how to write the sample in research

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• What is a sample in research: Definition, examples & tips

Researchers can conduct studies on large populations. It is highly unusual for researchers to be able to get information from every member of a group of individuals they are studying. If you are researching a large population, you can pick a sample . 

The population that will participate in the study is the sample. Using samples, researchers may perform their experiments more quickly and with more manageable data. This article will explain the definition of a sample in research, what a sample is in statistics with examples, how researchers choose a sample, and how to determine the correct sample size for your research with all details.

• What is a sample?

A sample is a condensed, controllable representation of a larger group . It is a subgroup of people with traits from a wider population . When the population size is too large for the test to include all potential participants or observations, samples are utilized in statistical testing. 

The definition of a sample

To put it simply:  a sample is a more manageable and compact version of a bigger group. A sampler population possesses the traits of a bigger group. A sample is utilized in statistical analysis when the population size is too big to include all individuals or observations in the test.

A sample is an analytical subset of a larger population in statistics . The sample should be representative of the population as a whole and should not show bias toward any particular characteristic. The researcher gains knowledge from the sample that can be applied to the entire population.  

• How do researchers choose a sample?

Sampling is an essential component of the research design as it gathers information that can be used in a research study. Probability sampling and non probability sampling are the essential methodologies that define sampling techniques. 

Sampling methodologies

Probability sampling

Probability sampling is a sampling technique that entails randomly picking a sample or a section of the population. It is also known as random sampling . When procedures are established to guarantee that each unit within a population has an equal probability of being picked , this is known as random selection.  Here are 4 types of probability sampling designs that are frequently used. 

1 - Simple random sampling

Simple random sampling takes a random selection from the whole population with an equal probability of selection for each unit. The most typical method of choosing a random sample is the one. 

Consider creating a list of every person in the population and giving them a number. Using a random number table, random number table, or random number generator, you choose samples at random from this population. 

2 - Stratified sampling

Stratified sampling randomly chooses a sample from one or more strata or population subgroups . Each group is distinguished from the others based on a shared trait, such as age, gender, color, and religion. 

By doing this, you can ensure that your sample population sufficiently represents each subgroup of a particular community. For example, if you divide a student population by university majors, Architecture, Linguistics, and Teaching departments, students are three different tiers within that population. 

3 - Cluster sampling

The cluster sampling method divides the population into clusters , which are smaller groupings. Then, you choose a sample of people at random from these clusters. Large or geographically distributed populations are frequently studied using cluster sampling. 

For example, you may divide all cities into neighborhoods or clusters and then choose the areas with the most significant population while filtering by mobile device users to see how well your goods perform across a city.

4 - Systematic sampling

When using systematic sampling , units are chosen at regular intervals beginning at a random point , drawing a random sample from the target population. Every member of the population is assigned a number in systematic sampling ,  but rather than being a random selection procedure, people are picked out at predetermined intervals. 

For example, while 1000 vaccine volunteers are selected from a list of 5000 applicants, each applicant is given a number from 1 to 5000. A sample of 1000 volunteers can then be obtained by starting at 1 and selecting each participant on 10 to an item scale.

Nonprobability sampling

When the number of units in the population is either unknown or difficult to identify individuals , nonprobability sampling approaches are utilized in quantitative and qualitative research. Additionally, it is employed when you wish to limit the results’ applicability to a particular group or organization rather than the broader populace. 

Besides the advantages of non-probability sampling, the most significant disadvantage is the possibility of sampling bias. As the sample selection process unfairly favors some population members over others. Here are some types of nonprobability sampling:

1. Convenience sampling

Convenience sampling comprises those who are easiest to research by the researcher. Researchers selected these samples only because they are simple to compile , and they did not think to choose a sample representative of the total population. 

For example, researchers conducted a shopping mall response survey to understand a product manufacturer's likelihood of customers using the products. In this sampling method, sample participants are selected based on their proximity to the survey table and their willingness to participate in the research.  

2. Snowball sampling

Snowball sampling is used to recruit participants through other participants if the population is difficult to reach. As you interact with additional individuals, your network of contacts "snowballs" in size.

For example, you are looking into local homeless people's experiences. Since there is no list of every homeless person in the city, probability sampling is not an option. One of the persons you meet agrees to participate in the research, and the homeless person refers you to other local homeless people he knows.

3. Purposive sampling

Purposive sampling is frequently employed in qualitative research when the researcher prefers to learn in-depth information about a particular phenomenon versus drawing general conclusions from statistics or when the population is relatively tiny and focused.

For instance, a researcher wants to learn more about how people with persistent headaches live. In such instances, they can choose a sample of people diagnosed with persistent headaches using purposive sampling. 

• How to determine the right sample size

The sample size is crucial for reliable, statistically meaningful results and a smooth research operation. You should learn the fundamentals of the statistics involved to select the appropriate sample size , considering a few distinct elements that may affect your study.

1. Population size

The population size is the total number of individuals that can be included in the study. To determine the appropriate population size, you should be clear about who belongs or doesn’t belong in your group. 

2. The margin of error (confidence interval)

Errors are inevitable in research studies. The margin of error is represented by a percentage, which is a statistical inference about the confidence that the number of respondents accurately represents the opinions of the whole population.  

3. Confidence level

The confidence level value measures your degree of certainty on how closely a sample reflects the total population within your chosen margin of error. The most prevalent are the 90%, 95%, and 99% confidence intervals.

4. Standard deviation

The standard deviation indicates how much variation you can expect in your responses. A safe value to use as a guide is 0.5 , which denotes that significant sample size is required.

Sample size formula

You may select the appropriate sample size by considering various factors affecting your study. You may compute the sample using an online calculator or read on to learn how to do it by hand.

1. Discover the Z-score

The Z-score displays how far a certain ratio deviates from the mean by standard deviation. You should translate your degree of confidence into a Z-score.

For the most typical confidence levels, the Z-scores are as follows:

• 90% Z-score = 1.645
• 95% Z-score = 1.96
• 99% Z-score = 2.576

2. Apply the formula for the sample size

Use the following formula to perform the calculation manually. 

• N = population size
•  e = Margin of error 
•  z = z-score
•  p = standard of deviation

For example, you select a 95% confidence level. Let the population size be 1000, and the margin of level be 5. Based on these data, your sample size would be 370.

• Frequently asked questions about sample

A sample is a particular group from which you will gather data. You should employ a sample when your population is sizable , spread geographically , or challenging . The population, sample, and sample frame are different from each other. Here are the frequently asked questions about the sample.

Population vs. sample

Sample and population are closely related concepts, so they can often be confused. We will explain the differences between them so that you can distinguish between the sample and population. 

Population refers to the entire group of individuals about which you want to draw conclusions. On the other hand, sample refers to the group of people you will collect data from.

A sample is more manageable, minor, and representative of a bigger group. The sample size is always less than the total population size. When a population is too vast for all the members or observations to be included in the test, a sample is employed in statistical analysis.

Sample vs. sample frame

A sample is a group of participants chosen from a broader population of interest; it is an essential component of the research. On the other hand, sample frames are crucial for  researchers to maintain organization and guarantee that the most recent data for a population is being used. Here are the differences between sample and sample frame: 

The sample is a smaller group of people or units chosen from a larger population for a survey or research project. In contrast, a sample frame is an exhaustive enumeration of all the elements or people that comprise the population from which the sample is taken. 

The sample is a subset of the population's elements chosen for research, whereas the sample frame is a comprehensive list or inventory of all population items.

• Key points to takeaway

In conclusion, a sample is a group or subset of persons or things chosen from a broader population to study or assess particular traits or behaviors. To guarantee that every member of the population has an equal chance of being chosen, the sample should be representative of the people from which it is collected or selected using a random sampling procedure. 

Selecting the appropriate sample technique based on the research topic , budget , and available resources . Additionally, the accuracy and generalizability of the results are greatly influenced by the sample size. 

This article has explained what a sample is in research methodology, what sample is in research examples, and how to determine the correct sample size. You can learn more about the research by reading this article.

Sena is a content writer at forms.app. She likes to read and write articles on different topics. Sena also likes to learn about different cultures and travel. She likes to study and learn different languages. Her specialty is linguistics, surveys, survey questions, and sampling methods.

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How to Write a Research Design – Guide with Examples

Published by Alaxendra Bets at August 14th, 2021 , Revised On June 24, 2024

A research design is a structure that combines different components of research. It involves the use of different data collection and data analysis techniques logically to answer the  research questions .

It would be best to make some decisions about addressing the research questions adequately before starting the research process, which is achieved with the help of the research design.

Below are the key aspects of the decision-making process:

• Data type required for research
• Research resources
• Participants required for research
• Hypothesis based upon research question(s)
• Data analysis  methodologies
• Variables (Independent, dependent, and confounding)
• The location and timescale for conducting the data
• The time period required for research

The research design provides the strategy of investigation for your project. Furthermore, it defines the parameters and criteria to compile the data to evaluate results and conclude.

Your project’s validity depends on the data collection and  interpretation techniques.  A strong research design reflects a strong  dissertation , scientific paper, or research proposal .

Step 1: Establish Priorities for Research Design

Before conducting any research study, you must address an important question: “how to create a research design.”

The research design depends on the researcher’s priorities and choices because every research has different priorities. For a complex research study involving multiple methods, you may choose to have more than one research design.

Multimethodology or multimethod research includes using more than one data collection method or research in a research study or set of related studies.

If one research design is weak in one area, then another research design can cover that weakness. For instance, a  dissertation analyzing different situations or cases will have more than one research design.

For example:

• Experimental research involves experimental investigation and laboratory experience, but it does not accurately investigate the real world.
• Quantitative research is good for the  statistical part of the project, but it may not provide an in-depth understanding of the  topic .
• Also, correlational research will not provide experimental results because it is a technique that assesses the statistical relationship between two variables.

While scientific considerations are a fundamental aspect of the research design, It is equally important that the researcher think practically before deciding on its structure. Here are some questions that you should think of;

• Do you have enough time to gather data and complete the write-up?
• Will you be able to collect the necessary data by interviewing a specific person or visiting a specific location?
• Do you have in-depth knowledge about the  different statistical analysis and data collection techniques to address the research questions  or test the  hypothesis ?

If you think that the chosen research design cannot answer the research questions properly, you can refine your research questions to gain better insight.

Step 2: Data Type you Need for Research

Decide on the type of data you need for your research. The type of data you need to collect depends on your research questions or research hypothesis. Two types of research data can be used to answer the research questions:

Primary Data Vs. Secondary Data

Qualitative Vs. Quantitative Data

Also, see; Research methods, design, and analysis .

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• Hire an expert from ResearchProspect today!
• Statistical analysis, research methodology, discussion of the results or conclusion – our experts can help you no matter how complex the requirements are.

Step 3: Data Collection Techniques

Once you have selected the type of research to answer your research question, you need to decide where and how to collect the data.

It is time to determine your research method to address the  research problem . Research methods involve procedures, techniques, materials, and tools used for the study.

For instance, a dissertation research design includes the different resources and data collection techniques and helps establish your  dissertation’s structure .

The following table shows the characteristics of the most popularly employed research methods.

Research Methods

Step 4: Procedure of Data Analysis

Use of the  correct data and statistical analysis technique is necessary for the validity of your research. Therefore, you need to be certain about the data type that would best address the research problem. Choosing an appropriate analysis method is the final step for the research design. It can be split into two main categories;

Quantitative Data Analysis

The quantitative data analysis technique involves analyzing the numerical data with the help of different applications such as; SPSS, STATA, Excel, origin lab, etc.

This data analysis strategy tests different variables such as spectrum, frequencies, averages, and more. The research question and the hypothesis must be established to identify the variables for testing.

Qualitative Data Analysis

Qualitative data analysis of figures, themes, and words allows for flexibility and the researcher’s subjective opinions. This means that the researcher’s primary focus will be interpreting patterns, tendencies, and accounts and understanding the implications and social framework.

You should be clear about your research objectives before starting to analyze the data. For example, you should ask yourself whether you need to explain respondents’ experiences and insights or do you also need to evaluate their responses with reference to a certain social framework.

Step 5: Write your Research Proposal

The research design is an important component of a research proposal because it plans the project’s execution. You can share it with the supervisor, who would evaluate the feasibility and capacity of the results  and  conclusion .

Read our guidelines to write a research proposal  if you have already formulated your research design. The research proposal is written in the future tense because you are writing your proposal before conducting research.

The  research methodology  or research design, on the other hand, is generally written in the past tense.

How to Write a Research Design – Conclusion

A research design is the plan, structure, strategy of investigation conceived to answer the research question and test the hypothesis. The dissertation research design can be classified based on the type of data and the type of analysis.

Above mentioned five steps are the answer to how to write a research design. So, follow these steps to  formulate the perfect research design for your dissertation .

ResearchProspect writers have years of experience creating research designs that align with the dissertation’s aim and objectives. If you are struggling with your dissertation methodology chapter, you might want to look at our dissertation part-writing service.

Our dissertation writers can also help you with the full dissertation paper . No matter how urgent or complex your need may be, ResearchProspect can help. We also offer PhD level research paper writing services.

Frequently Asked Questions

What is research design.

Research design is a systematic plan that guides the research process, outlining the methodology and procedures for collecting and analysing data. It determines the structure of the study, ensuring the research question is answered effectively, reliably, and validly. It serves as the blueprint for the entire research project.

How to write a research design?

To write a research design, define your research question, identify the research method (qualitative, quantitative, or mixed), choose data collection techniques (e.g., surveys, interviews), determine the sample size and sampling method, outline data analysis procedures, and highlight potential limitations and ethical considerations for the study.

How to write the design section of a research paper?

In the design section of a research paper, describe the research methodology chosen and justify its selection. Outline the data collection methods, participants or samples, instruments used, and procedures followed. Detail any experimental controls, if applicable. Ensure clarity and precision to enable replication of the study by other researchers.

How to write a research design in methodology?

To write a research design in methodology, clearly outline the research strategy (e.g., experimental, survey, case study). Describe the sampling technique, participants, and data collection methods. Detail the procedures for data collection and analysis. Justify choices by linking them to research objectives, addressing reliability and validity.

You May Also Like

Struggling to find relevant and up-to-date topics for your dissertation? Here is all you need to know if unsure about how to choose dissertation topic.

Repository of ten perfect research question examples will provide you a better perspective about how to create research questions.

How to write a hypothesis for dissertation,? A hypothesis is a statement that can be tested with the help of experimental or theoretical research.

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Introduction to Research Methods

7 samples and populations.

So you’ve developed your research question, figured out how you’re going to measure whatever you want to study, and have your survey or interviews ready to go. Now all your need is other people to become your data.

You might say ‘easy!’, there’s people all around you. You have a big family tree and surely them and their friends would have happy to take your survey. And then there’s your friends and people you’re in class with. Finding people is way easier than writing the interview questions or developing the survey. That reaction might be a strawman, maybe you’ve come to the conclusion none of this is easy. For your data to be valuable, you not only have to ask the right questions, you have to ask the right people. The “right people” aren’t the best or the smartest people, the right people are driven by what your study is trying to answer and the method you’re using to answer it.

Remember way back in chapter 2 when we looked at this chart and discussed the differences between qualitative and quantitative data.

One of the biggest differences between quantitative and qualitative data was whether we wanted to be able to explain something for a lot of people (what percentage of residents in Oklahoma support legalizing marijuana?) versus explaining the reasons for those opinions (why do some people support legalizing marijuana and others not?). The underlying differences there is whether our goal is explain something about everyone, or whether we’re content to explain it about just our respondents.

‘Everyone’ is called the population . The population in research is whatever group the research is trying to answer questions about. The population could be everyone on planet Earth, everyone in the United States, everyone in rural counties of Iowa, everyone at your university, and on and on. It is simply everyone within the unit you are intending to study.

In order to study the population, we typically take a sample or a subset. A sample is simply a smaller number of people from the population that are studied, which we can use to then understand the characteristics of the population based on that subset. That’s why a poll of 1300 likely voters can be used to guess at who will win your states Governor race. It isn’t perfect, and we’ll talk about the math behind all of it in a later chapter, but for now we’ll just focus on the different types of samples you might use to study a population with a survey.

If correctly sampled, we can use the sample to generalize information we get to the population. Generalizability , which we defined earlier, means we can assume the responses of people to our study match the responses everyone would have given us. We can only do that if the sample is representative of the population, meaning that they are alike on important characteristics such as race, gender, age, education. If something makes a large difference in people’s views on a topic in your research and your sample is not balanced, you’ll get inaccurate results.

Generalizability is more of a concern with surveys than with interviews. The goal of a survey is to explain something about people beyond the sample you get responses from. You’ll never see a news headline saying that “53% of 1250 Americans that responded to a poll approve of the President”. It’s only worth asking those 1250 people if we can assume the rest of the United States feels the same way overall. With interviews though we’re looking for depth from their responses, and so we are less hopefully that the 15 people we talk to will exactly match the American population. That doesn’t mean the data we collect from interviews doesn’t have value, it just has different uses.

There are two broad types of samples, with several different techniques clustered below those. Probability sampling is associated with surveys, and non-probability sampling is often used when conducting interviews. We’ll first describe probability samples, before discussing the non-probability options.

The type of sampling you’ll use will be based on the type of research you’re intending to do. There’s no sample that’s right or wrong, they can just be more or less appropriate for the question you’re trying to answer. And if you use a less appropriate sampling strategy, the answer you get through your research is less likely to be accurate.

7.1 Types of Probability Samples

So we just hinted at the idea that depending on the sample you use, you can generalize the data you collect from the sample to the population. That will depend though on whether your sample represents the population. To ensure that your sample is representative of the population, you will want to use a probability sample. A representative sample refers to whether the characteristics (race, age, income, education, etc) of the sample are the same as the population. Probability sampling is a sampling technique in which every individual in the population has an equal chance of being selected as a subject for the research.

There are several different types of probability samples you can use, depending on the resources you have available.

Let’s start with a simple random sample . In order to use a simple random sample all you have to do is take everyone in your population, throw them in a hat (not literally, you can just throw their names in a hat), and choose the number of names you want to use for your sample. By drawing blindly, you can eliminate human bias in constructing the sample and your sample should represent the population from which it is being taken.

However, a simple random sample isn’t quite that easy to build. The biggest issue is that you have to know who everyone is in order to randomly select them. What that requires is a sampling frame , a list of all residents in the population. But we don’t always have that. There is no list of residents of New York City (or any other city). Organizations that do have such a list wont just give it away. Try to ask your university for a list and contact information of everyone at your school so you can do a survey? They wont give it to you, for privacy reasons. It’s actually harder to think of popultions you could easily develop a sample frame for than those you can’t. If you can get or build a sampling frame, the work of a simple random sample is fairly simple, but that’s the biggest challenge.

Most of the time a true sampling frame is impossible to acquire, so researcher have to settle for something approximating a complete list. Earlier generations of researchers could use the random dial method to contact a random sample of Americans, because every household had a single phone. To use it you just pick up the phone and dial random numbers. Assuming the numbers are actually random, anyone might be called. That method actually worked somewhat well, until people stopped having home phone numbers and eventually stopped answering the phone. It’s a fun mental exercise to think about how you would go about creating a sampling frame for different groups though; think through where you would look to find a list of everyone in these groups:

Plumbers Recent first-time fathers Members of gyms

The best way to get an actual sampling frame is likely to purchase one from a private company that buys data on people from all the different websites we use.

Let’s say you do have a sampling frame though. For instance, you might be hired to do a survey of members of the Republican Party in the state of Utah to understand their political priorities this year, and the organization could give you a list of their members because they’ve hired you to do the reserach. One method of constructing a simple random sample would be to assign each name on the list a number, and then produce a list of random numbers. Once you’ve matched the random numbers to the list, you’ve got your sample. See the example using the list of 20 names below

and the list of 5 random numbers.

Systematic sampling is similar to simple random sampling in that it begins with a list of the population, but instead of choosing random numbers one would select every kth name on the list. What the heck is a kth? K just refers to how far apart the names are on the list you’re selecting. So if you want to sample one-tenth of the population, you’d select every tenth name. In order to know the k for your study you need to know your sample size (say 1000) and the size of the population (75000). You can divide the size of the population by the sample (75000/1000), which will produce your k (750). As long as the list does not contain any hidden order, this sampling method is as good as the random sampling method, but its only advantage over the random sampling technique is simplicity. If we used the same list as above and wanted to survey 1/5th of the population, we’d include 4 of the names on the list. It’s important with systematic samples to randomize the starting point in the list, otherwise people with A names will be oversampled. If we started with the 3rd name, we’d select Annabelle Frye, Cristobal Padilla, Jennie Vang, and Virginia Guzman, as shown below. So in order to use a systematic sample, we need three things, the population size (denoted as N ), the sample size we want ( n ) and k , which we calculate by dividing the population by the sample).

N= 20 (Population Size) n= 4 (Sample Size) k= 5 {20/4 (kth element) selection interval}

We can also use a stratified sample , but that requires knowing more about the population than just their names. A stratified sample divides the study population into relevant subgroups, and then draws a sample from each subgroup. Stratified sampling can be used if you’re very concerned about ensuring balance in the sample or there may be a problem of underrepresentation among certain groups when responses are received. Not everyone in your sample is equally likely to answer a survey. Say for instance we’re trying to predict who will win an election in a county with three cities. In city A there are 1 million college students, in city B there are 2 million families, and in City C there are 3 million retirees. You know that retirees are more likely than busy college students or parents to respond to a poll. So you break the sample into three parts, ensuring that you get 100 responses from City A, 200 from City B, and 300 from City C, so the three cities would match the population. A stratified sample provides the researcher control over the subgroups that are included in the sample, whereas simple random sampling does not guarantee that any one type of person will be included in the final sample. A disadvantage is that it is more complex to organize and analyze the results compared to simple random sampling.

Cluster sampling is an approach that begins by sampling groups (or clusters) of population elements and then selects elements from within those groups. A researcher would use cluster sampling if getting access to elements in an entrie population is too challenging. For instance, a study on students in schools would probably benefit from randomly selecting from all students at the 36 elementary schools in a fictional city. But getting contact information for all students would be very difficult. So the researcher might work with principals at several schools and survey those students. The researcher would need to ensure that the students surveyed at the schools are similar to students throughout the entire city, and greater access and participation within each cluster may make that possible.

The image below shows how this can work, although the example is oversimplified. Say we have 12 students that are in 6 classrooms. The school is in total 1/4th green (3/12), 1/4th yellow (3/12), and half blue (6/12). By selecting the right clusters from within the school our sample can be representative of the entire school, assuming these colors are the only significant difference between the students. In the real world, you’d want to match the clusters and population based on race, gender, age, income, etc. And I should point out that this is an overly simplified example. What if 5/12s of the school was yellow and 1/12th was green, how would I get the right proportions? I couldn’t, but you’d do the best you could. You still wouldn’t want 4 yellows in the sample, you’d just try to approximiate the population characteristics as best you can.

7.2 Actually Doing a Survey

All of that probably sounds pretty complicated. Identifying your population shouldn’t be too difficult, but how would you ever get a sampling frame? And then actually identifying who to include… It’s probably a bit overwhelming and makes doing a good survey sound impossible.

Researchers using surveys aren’t superhuman though. Often times, they use a little help. Because surveys are really valuable, and because researchers rely on them pretty often, there has been substantial growth in companies that can help to get one’s survey to its intended audience.

One popular resource is Amazon’s Mechanical Turk (more commonly known as MTurk). MTurk is at its most basic a website where workers look for jobs (called hits) to be listed by employers, and choose whether to do the task or not for a set reward. MTurk has grown over the last decade to be a common source of survey participants in the social sciences, in part because hiring workers costs very little (you can get some surveys completed for penny’s). That means you can get your survey completed with a small grant ($1-2k at the low end) and get the data back in a few hours. Really, it’s a quick and easy way to run a survey.

However, the workers aren’t perfectly representative of the average American. For instance, researchers have found that MTurk respondents are younger, better educated, and earn less than the average American.

One way to get around that issue, which can be used with MTurk or any survey, is to weight the responses. Because with MTurk you’ll get fewer responses from older, less educated, and richer Americans, those responses you do give you want to count for more to make your sample more representative of the population. Oversimplified example incoming!

Imagine you’re setting up a pizza party for your class. There are 9 people in your class, 4 men and 5 women. You only got 4 responses from the men, and 3 from the women. All 4 men wanted peperoni pizza, while the 3 women want a combination. Pepperoni wins right, 4 to 3? Not if you assume that the people that didn’t respond are the same as the ones that did. If you weight the responses to match the population (the full class of 9), a combination pizza is the winner.

Because you know the population of women is 5, you can weight the 3 responses from women by 5/3 = 1.6667. If we weight (or multiply) each vote we did receive from a woman by 1.6667, each vote for a combination now equals 1.6667, meaning that the 3 votes for combination total 5. Because we received a vote from every man in the class, we just weight their votes by 1. The big assumption we have to make is that the people we didn’t hear from (the 2 women that didn’t vote) are similar to the ones we did hear from. And if we don’t get any responses from a group we don’t have anything to infer their preferences or views from.

Let’s go through a slightly more complex example, still just considering one quality about people in the class. Let’s say your class actually has 100 students, but you only received votes from 50. And, what type of pizza people voted for is mixed, but men still prefer peperoni overall, and women still prefer combination. The class is 60% female and 40% male.

We received 21 votes from women out of the 60, so we can weight their responses by 60/21 to represent the population. We got 29 votes out of the 40 for men, so their responses can be weighted by 40/29. See the math below.

53.8 votes for combination? That might seem a little odd, but weighting isn’t a perfect science. We can’t identify what a non-respondent would have said exactly, all we can do is use the responses of other similar people to make a good guess. That issue often comes up in polling, where pollsters have to guess who is going to vote in a given election in order to project who will win. And we can weight on any characteristic of a person we think will be important, alone or in combination. Modern polls weight on age, gender, voting habits, education, and more to make the results as generalizable as possible.

There’s an appendix later in this book where I walk through the actual steps of creating weights for a sample in R, if anyone actually does a survey. I intended this section to show that doing a good survey might be simpler than it seemed, but now it might sound even more difficult. A good lesson to take though is that there’s always another door to go through, another hurdle to improve your methods. Being good at research just means being constantly prepared to be given a new challenge, and being able to find another solution.

7.3 Non-Probability Sampling

Qualitative researchers’ main objective is to gain an in-depth understanding on the subject matter they are studying, rather than attempting to generalize results to the population. As such, non-probability sampling is more common because of the researchers desire to gain information not from random elements of the population, but rather from specific individuals.

Random selection is not used in nonprobability sampling. Instead, the personal judgment of the researcher determines who will be included in the sample. Typically, researchers may base their selection on availability, quotas, or other criteria. However, not all members of the population are given an equal chance to be included in the sample. This nonrandom approach results in not knowing whether the sample represents the entire population. Consequently, researchers are not able to make valid generalizations about the population.

As with probability sampling, there are several types of non-probability samples. Convenience sampling , also known as accidental or opportunity sampling, is a process of choosing a sample that is easily accessible and readily available to the researcher. Researchers tend to collect samples from convenient locations such as their place of employment, a location, school, or other close affiliation. Although this technique allows for quick and easy access to available participants, a large part of the population is excluded from the sample.

For example, researchers (particularly in psychology) often rely on research subjects that are at their universities. That is highly convenient, students are cheap to hire and readily available on campuses. However, it means the results of the study may have limited ability to predict motivations or behaviors of people that aren’t included in the sample, i.e., people outside the age of 18-22 that are going to college.

If I ask you to get find out whether people approve of the mayor or not, and tell you I want 500 people’s opinions, should you go stand in front of the local grocery store? That would be convinient, and the people coming will be random, right? Not really. If you stand outside a rural Piggly Wiggly or an urban Whole Foods, do you think you’ll see the same people? Probably not, people’s chracteristics make the more or less likely to be in those locations. This technique runs the high risk of over- or under-representation, biased results, as well as an inability to make generalizations about the larger population. As the name implies though, it is convenient.

Purposive sampling , also known as judgmental or selective sampling, refers to a method in which the researcher decides who will be selected for the sample based on who or what is relevant to the study’s purpose. The researcher must first identify a specific characteristic of the population that can best help answer the research question. Then, they can deliberately select a sample that meets that particular criterion. Typically, the sample is small with very specific experiences and perspectives. For instance, if I wanted to understand the experiences of prominent foreign-born politicians in the United States, I would purposefully build a sample of… prominent foreign-born politicians in the United States. That would exclude anyone that was born in the United States or and that wasn’t a politician, and I’d have to define what I meant by prominent. Purposive sampling is susceptible to errors in judgment by the researcher and selection bias due to a lack of random sampling, but when attempting to research small communities it can be effective.

When dealing with small and difficult to reach communities researchers sometimes use snowball samples , also known as chain referral sampling. Snowball sampling is a process in which the researcher selects an initial participant for the sample, then asks that participant to recruit or refer additional participants who have similar traits as them. The cycle continues until the needed sample size is obtained.

This technique is used when the study calls for participants who are hard to find because of a unique or rare quality or when a participant does not want to be found because they are part of a stigmatized group or behavior. Examples may include people with rare diseases, sex workers, or a child sex offenders. It would be impossible to find an accurate list of sex workers anywhere, and surveying the general population about whether that is their job will produce false responses as people will be unwilling to identify themselves. As such, a common method is to gain the trust of one individual within the community, who can then introduce you to others. It is important that the researcher builds rapport and gains trust so that participants can be comfortable contributing to the study, but that must also be balanced by mainting objectivity in the research.

Snowball sampling is a useful method for locating hard to reach populations but cannot guarantee a representative sample because each contact will be based upon your last. For instance, let’s say you’re studying illegal fight clubs in your state. Some fight clubs allow weapons in the fights, while others completely ban them; those two types of clubs never interreact because of their disagreement about whether weapons should be allowed, and there’s no overlap between them (no members in both type of club). If your initial contact is with a club that uses weapons, all of your subsequent contacts will be within that community and so you’ll never understand the differences. If you didn’t know there were two types of clubs when you started, you’ll never even know you’re only researching half of the community. As such, snowball sampling can be a necessary technique when there are no other options, but it does have limitations.

Quota Sampling is a process in which the researcher must first divide a population into mutually exclusive subgroups, similar to stratified sampling. Depending on what is relevant to the study, subgroups can be based on a known characteristic such as age, race, gender, etc. Secondly, the researcher must select a sample from each subgroup to fit their predefined quotas. Quota sampling is used for the same reason as stratified sampling, to ensure that your sample has representation of certain groups. For instance, let’s say that you’re studying sexual harassment in the workplace, and men are much more willing to discuss their experiences than women. You might choose to decide that half of your final sample will be women, and stop requesting interviews with men once you fill your quota. The core difference is that while stratified sampling chooses randomly from within the different groups, quota sampling does not. A quota sample can either be proportional or non-proportional . Proportional quota sampling refers to ensuring that the quotas in the sample match the population (if 35% of the company is female, 35% of the sample should be female). Non-proportional sampling allows you to select your own quota sizes. If you think the experiences of females with sexual harassment are more important to your research, you can include whatever percentage of females you desire.

7.4 Dangers in sampling

Now that we’ve described all the different ways that one could create a sample, we can talk more about the pitfalls of sampling. Ensuring a quality sample means asking yourself some basic questions:

• Who is in the sample?
• How were they sampled?
• Why were they sampled?

A meal is often only as good as the ingredients you use, and your data will only be as good as the sample. If you collect data from the wrong people, you’ll get the wrong answer. You’ll still get an answer, it’ll just be inaccurate. And I want to reemphasize here wrong people just refers to inappropriate for your study. If I want to study bullying in middle schools, but I only talk to people that live in a retirement home, how accurate or relevant will the information I gather be? Sure, they might have grandchildren in middle school, and they may remember their experiences. But wouldn’t my information be more relevant if I talked to students in middle school, or perhaps a mix of teachers, parents, and students? I’ll get an answer from retirees, but it wont be the one I need. The sample has to be appropriate to the research question.

Is a bigger sample always better? Not necessarily. A larger sample can be useful, but a more representative one of the population is better. That was made painfully clear when the magazine Literary Digest ran a poll to predict who would win the 1936 presidential election between Alf Landon and incumbent Franklin Roosevelt. Literary Digest had run the poll since 1916, and had been correct in predicting the outcome every time. It was the largest poll ever, and they received responses for 2.27 million people. They essentially received responses from 1 percent of the American population, while many modern polls use only 1000 responses for a much more populous country. What did they predict? They showed that Alf Landon would be the overwhelming winner, yet when the election was held Roosevelt won every state except Maine and Vermont. It was one of the most decisive victories in Presidential history.

So what went wrong for the Literary Digest? Their poll was large (gigantic!), but it wasn’t representative of likely voters. They polled their own readership, which tended to be more educated and wealthy on average, along with people on a list of those with registered automobiles and telephone users (both of which tended to be owned by the wealthy at that time). Thus, the poll largely ignored the majority of Americans, who ended up voting for Roosevelt. The Literary Digest poll is famous for being wrong, but led to significant improvements in the science of polling to avoid similar mistakes in the future. Researchers have learned a lot in the century since that mistake, even if polling and surveys still aren’t (and can’t be) perfect.

What kind of sampling strategy did Literary Digest use? Convenience, they relied on lists they had available, rather than try to ensure every American was included on their list. A representative poll of 2 million people will give you more accurate results than a representative poll of 2 thousand, but I’ll take the smaller more representative poll than a larger one that uses convenience sampling any day.

7.5 Summary

Picking the right type of sample is critical to getting an accurate answer to your reserach question. There are a lot of differnet options in how you can select the people to participate in your research, but typically only one that is both correct and possible depending on the research you’re doing. In the next chapter we’ll talk about a few other methods for conducting reseach, some that don’t include any sampling by you.

• Cookies & Privacy
• GETTING STARTED
• Introduction
• FUNDAMENTALS
• Acknowledgements
• Research questions & hypotheses
• Concepts, constructs & variables
• Research limitations
• Getting started
• Sampling Strategy
• Research Quality
• Research Ethics
• Data Analysis

How to structure the Sampling Strategy section of your dissertation

The Sampling Strategy section of your Research Strategy chapter (usually Chapter Three: Research Strategy ) needs to be well structured. A good structure involves four steps : describing , explaining , stating and justifying . You need to: (1) describe what you are studying, including the units involved in your sample and the target population ; (2) explain the types of sampling technique available to you; (3) state and describe the sampling strategy you used; and (4) justify your choice of sampling strategy. In this article, we explain each of these four steps:

• STEP ONE: Describe what you are studying
• STEP TWO: Explain the types of sampling technique available to you
• STEP THREE: State and describe the sampling strategy you used
• STEP FOUR: Justify your choice of sampling strategy

STEP ONE Describe what you are studying

First, the reader needs to know what you studied. This should include details about the following:

The units you measured (or examined).

Your target population .

If you used a probability sampling technique to select your sample , you will also need to describe:

Your sampling frame .

If you are unsure what of any of these terms mean (i.e., unit , sampling frame , population ), you might want to read the article, Sampling: The basics , before reading on. If you feel comfortable with these terms, let's imagine we completed a dissertation on the career choices of students at the University of Oxford, England. Below we describe our units , target population and sampling frame (imagining that we used a probability sampling technique ).

Career choices of students at the University of Oxford, England We examined the career choices of all students at the University of Oxford, England. By all students we mean all undergraduate and postgraduate students, full-time and part-time, studying at the University of Oxford, England, enrolled as of 05 January 2011.

From this description , the reader learns the following:

Units: students Population: all undergraduate and postgraduate students, full-time and part-time, at the University of Oxford, England Sampling frame: all students enrolled at the University of Oxford, as of 05 January 2011 (i.e., according to Student Records, assuming this is the department that maintains a list of all students studying at the university)

Note the difference between the target population and the sampling frame, from which we select our sample (when using a probability sampling technique). They are the same in all respects apart from the fact that the sampling frame tells the reader that only those students enrolled in the university according to Student Records on a particular date (i.e., 05 January 2011) are being studied. If the list of students kept by Student Records is very different from the population of all students studying at the university, this should be made clear [see the article, Sampling: The basics, to understand more about sampling frames and potential sampling bias].

By the time you come to write up the Sampling Strategy section of your Research Strategy chapter, you should know whether the sampling frame is the same as the population. If it is not, you should highlight the difference between the two. This completes the first part of the Sampling Strategy section of your Research Strategy chapter.

STEP TWO Explain the types of sampling technique available to you

Once you know what units you are studying, as well as your population and sampling frame , the reader will often want to know what types of sampling technique you could use . We say could use rather than should use because whilst there are certain ideal choices of sampling technique, there is seldom a right or wrong answer. Instead, researchers choose sampling techniques that they feel are most appropriate to their study, based on theoretical and practical reasons.

Broadly speaking, you could choose to select your sample from (a) your sampling frame using either a probability sampling technique (e.g., simple random sampling, systematic random sampling, stratified random sampling) or (b) from your population using a non-probability sampling technique (e.g., quota sampling, purposive sampling, convenience sampling, snowball sampling). To understand the differences between these techniques, as well as their advantages and disadvantages, you may want to start by reading the articles: Probability sampling and Non-probability sampling .

When explaining the types of sampling technique that were available to you in this part of your Sampling Strategy section, you should take into account: (a) the research strategy guiding your dissertation; and (b) theoretical and practical sampling issues.

The research strategy guiding your dissertation

Theoretically , the ideal sampling technique for a piece of research (i.e., probability or non-probability sampling) differs depending on whether you are using a quantitative , qualitative or mixed methods research design .

Theoretical and practical sampling issues

Whilst there are theoretical ideals when it comes to choosing a sampling technique to use for your dissertation (i.e., probability or non-probability sampling), it is often practical issues that determine not only whether you choose one type of sampling technique over another (e.g., non-probability sampling over probability sampling ), but also the specific technique that you use (e.g., purposive sampling over quota sampling ; i.e., both are non-probability sampling techniques). Such practical issues range from whether your target population is known (i.e., whether you can get access to a list of the population) to whether you have the time and money to get access to such a list [click on the relevant article to understand the advantages and disadvantages (i.e., theoretical and practical considerations ) of the different probability sampling (e.g., simple random sampling , systematic random sampling , stratified random sampling ) and non-probability sampling techniques (e.g., quota sampling , purposive sampling , self-selection sampling , convenience sampling , snowball sampling )].

Assuming that you understand the differences between these sampling techniques, and their relative merits, let's consider what sampling choices are open to us using our example of career choices of students at the University of Oxford, England . The green text illustrates what we have already written above.

Career choices of students at the University of Oxford, England We examined the career choices of all students at the University of Oxford, England. By all students we mean all undergraduate and postgraduate students, full-time and part-time, studying at the University of Oxford, England, enrolled as of 05 January 2011. Since our research drew on a quantitative research design , the ideal would have been to use a probability sampling technique because this allows us to make statistical inferences (i.e., generalisations ) from our sample of students to all students at the university . Such a probability sampling technique would provide greater external validity for our findings. Since we wanted to compare the career choices of different strata (i.e., groups of students); more specifically, males and females , the appropriate choice of probability sampling technique would have been a stratified random sample . However, if it were not possible to use a probability sampling technique , we could have used a non-probability sampling technique . Since we wanted to compare different strata (i.e., groups of students) and achieve a sample that is as representative as possible of our population , we could have used a quota sample .

From this explanation , the reader learns the following:

Types of sampling strategy available: probability and non-probability sampling Ideal choice: probability sampling Preferred choice of probability sampling technique: stratified random sample Preferred choice of non-probability sampling technique: quota sample

When you are writing up this part of the Sampling Strategy section of your Research Strategy chapter, you may be expected to include a much more comprehensive list of reasons why you prefer one type of sampling strategy (i.e., probability or non-probability) and more specifically, a particular sampling technique (e.g., stratified random sampling over quota sampling). We provide information about the advantages and disadvantages of these different sampling strategies and sampling techniques in the following articles: for probability sampling , see simple random sampling , systematic random sampling , stratified random sampling ; for non-probability sampling techniques, see quota sampling , purposive sampling , self-selection sampling , convenience sampling , snowball sampling .

STEP THREE State and describe the sampling strategy you used

Third, you need to state what sampling strategy and sampling technique you used, describing what you did.

Again, let's consider this for our example of career choices of students at the University of Oxford, England . The green text illustrates what we have already written above.

Career choices of students at the University of Oxford, England We examined the career choices of all students at the University of Oxford, England. By all students we mean all undergraduate and postgraduate students, full-time and part-time, studying at the University of Oxford, England, enrolled as of 05 January 2011. Since our research drew on a quantitative research design , the ideal would have been to use a probability sampling technique because this allows us to make statistical inferences (i.e., generalisations ) from our sample of students to all students at the university. Such a probability sampling technique would provide greater external validity for our findings. Since we wanted to compare the career choices of different strata (i.e., groups of students), including males and females , the appropriate choice of probability sampling technique would have been a stratified random sample . However, if it were not possible to use a probability sampling technique , we could have used a non-probability sampling technique . Since we wanted to compare different strata (i.e., groups of students) and achieve a sample that is as representative as possible of our population , we could have used a quota sample . In the event, we used quota sampling to select the sample of students that would be invited to take part in our dissertation research. Student Records provided us with the appropriate quotas for male and female students, which showed a 53:47 male-female ration [ NOTE: this is a fictitious figure]. We selected a sample size of 200 students, which was based on subjective judgement and practicalities of cost and time. Therefore, we sampled 106 male students (i.e., 53% of our sample size of 200 students) and 94 female students (i.e., 47% of our sample size of 200 students). For convenience, we stood outside the main library where we felt the thoroughfare (i.e., number of students passing by) would be highest.

From this statement and description , the reader learns the following:

Sampling strategy chosen: non-probability sampling Specific sampling technique used: quota sampling

Details of quota sampling: strata (i.e., groups of students) of interest are males and females ratio of males-females at the university was 53:47 sample size selected was 200 students quota sample filled based on ease of access to students at the main university library.

Again, when you are writing up this part of the Sampling Strategy section of your Research Strategy chapter, it may be appropriate to include greater description of the sampling technique you used.

STEP FOUR Justify your choice of sampling strategy

Finally, you need to justify your choice of sampling strategy. When writing up the Sampling Strategy section of your Research Strategy chapter, you may find it easier to combine the third and fourth steps (i.e., stating and describing the sampling strategy you used, as well as justifying that choice). Taking our example of the career choices of students at the University of Oxford, England , we illustrate how the two steps can be integrated. As before, the green text illustrates what we have already written above.

Career choices of students at the University of Oxford, England We examined the career choices of all students at the University of Oxford, England. By all students we mean all undergraduate and postgraduate students, full-time and part-time, studying at the University of Oxford, England, enrolled as of 05 January 2011. Since our research drew on a quantitative research design , the ideal would have been to use a probability sampling technique because this allows us to make statistical inferences (i.e., generalisations ) from our sample of students to all students at the university. Such a probability sampling technique would provide greater external validity for our findings. Since we wanted to compare the career choices of different strata (i.e., groups of students), including males and females , the appropriate choice of probability sampling technique would have been a stratified random sample . However, if it were not possible to use a probability sampling technique , we could have used a non-probability sampling technique . Since we wanted to compare different strata (i.e., groups of students) and achieve a sample that is as representative as possible of our population , we could have used a quota sample . In the event, we used quota sampling to select the sample of students that would be invited to take part in our dissertation research. We were unable to use a stratified random sampling , our preferred choice, because we could not obtain permission from Student Records to access a complete list of all students at the university. Without any other way of attaining a list of all students, we had to use quota sampling . However, Student Records did provide us with the appropriate quotas for male and female students, which showed a 53:47 male-female ration [note: this is a fictitious figure]. We selected a sample size of 200 students, which was based on subjective judgement and practicalities of cost and time. Therefore, we sampled 106 male students (i.e., 53% of our sample size of 200 students) and 94 female students (i.e., 47% of our sample size of 200 students). For convenience, we stood outside the main library where we felt the thoroughfare (i.e., number of students passing by) would be highest.

From this justification , the reader learns the following:

Main reason for rejecting the ideal sampling strategy:

Access to a list of all students (i.e., the sampling frame needed for probability sampling ) was not granted by Student Records.

No other way of attaining a list of all students was available.

When you think about justifying your choice of sampling technique when writing up the Sampling Strategy section of your Research Strategy chapter, you should consider both practical reasons (e.g., what time you have available, what access you have, etc.) and theoretical reasons (i.e., those relating to the specific sampling technique , but also your choice of research paradigm , research design and research methods ).

How to Write a Research Question: Types and Examples 

The first step in any research project is framing the research question. It can be considered the core of any systematic investigation as the research outcomes are tied to asking the right questions. Thus, this primary interrogation point sets the pace for your research as it helps collect relevant and insightful information that ultimately influences your work.   

Typically, the research question guides the stages of inquiry, analysis, and reporting. Depending on the use of quantifiable or quantitative data, research questions are broadly categorized into quantitative or qualitative research questions. Both types of research questions can be used independently or together, considering the overall focus and objectives of your research.  

What is a research question?

A research question is a clear, focused, concise, and arguable question on which your research and writing are centered. 1 It states various aspects of the study, including the population and variables to be studied and the problem the study addresses. These questions also set the boundaries of the study, ensuring cohesion. 

Designing the research question is a dynamic process where the researcher can change or refine the research question as they review related literature and develop a framework for the study. Depending on the scale of your research, the study can include single or multiple research questions. 

A good research question has the following features: 

• It is relevant to the chosen field of study. 
• The question posed is arguable and open for debate, requiring synthesizing and analysis of ideas. 
• It is focused and concisely framed. 
• A feasible solution is possible within the given practical constraint and timeframe. 

A poorly formulated research question poses several risks. 1   

• Researchers can adopt an erroneous design. 
• It can create confusion and hinder the thought process, including developing a clear protocol.  
• It can jeopardize publication efforts.  
• It causes difficulty in determining the relevance of the study findings.  
• It causes difficulty in whether the study fulfils the inclusion criteria for systematic review and meta-analysis. This creates challenges in determining whether additional studies or data collection is needed to answer the question.  
• Readers may fail to understand the objective of the study. This reduces the likelihood of the study being cited by others. 

Now that you know “What is a research question?”, let’s look at the different types of research questions. 

Types of research questions

Depending on the type of research to be done, research questions can be classified broadly into quantitative, qualitative, or mixed-methods studies. Knowing the type of research helps determine the best type of research question that reflects the direction and epistemological underpinnings of your research. 

The structure and wording of quantitative 2 and qualitative research 3 questions differ significantly. The quantitative study looks at causal relationships, whereas the qualitative study aims at exploring a phenomenon. 

• Quantitative research questions:  
• Seeks to investigate social, familial, or educational experiences or processes in a particular context and/or location.  
• Answers ‘how,’ ‘what,’ or ‘why’ questions. 
• Investigates connections, relations, or comparisons between independent and dependent variables. 

Quantitative research questions can be further categorized into descriptive, comparative, and relationship, as explained in the Table below. 

• Qualitative research questions  

Qualitative research questions are adaptable, non-directional, and more flexible. It concerns broad areas of research or more specific areas of study to discover, explain, or explore a phenomenon. These are further classified as follows: 

• Mixed-methods studies  

Mixed-methods studies use both quantitative and qualitative research questions to answer your research question. Mixed methods provide a complete picture than standalone quantitative or qualitative research, as it integrates the benefits of both methods. Mixed methods research is often used in multidisciplinary settings and complex situational or societal research, especially in the behavioral, health, and social science fields. 

What makes a good research question

A good research question should be clear and focused to guide your research. It should synthesize multiple sources to present your unique argument, and should ideally be something that you are interested in. But avoid questions that can be answered in a few factual statements. The following are the main attributes of a good research question. 

• Specific: The research question should not be a fishing expedition performed in the hopes that some new information will be found that will benefit the researcher. The central research question should work with your research problem to keep your work focused. If using multiple questions, they should all tie back to the central aim. 
• Measurable: The research question must be answerable using quantitative and/or qualitative data or from scholarly sources to develop your research question. If such data is impossible to access, it is better to rethink your question. 
• Attainable: Ensure you have enough time and resources to do all research required to answer your question. If it seems you will not be able to gain access to the data you need, consider narrowing down your question to be more specific. 
• You have the expertise 
• You have the equipment and resources 
• Realistic: Developing your research question should be based on initial reading about your topic. It should focus on addressing a problem or gap in the existing knowledge in your field or discipline. 
• Based on some sort of rational physics 
• Can be done in a reasonable time frame 
• Timely: The research question should contribute to an existing and current debate in your field or in society at large. It should produce knowledge that future researchers or practitioners can later build on. 
• Novel 
• Based on current technologies. 
• Important to answer current problems or concerns. 
• Lead to new directions. 
• Important: Your question should have some aspect of originality. Incremental research is as important as exploring disruptive technologies. For example, you can focus on a specific location or explore a new angle. 
• Meaningful whether the answer is “Yes” or “No.” Closed-ended, yes/no questions are too simple to work as good research questions. Such questions do not provide enough scope for robust investigation and discussion. A good research question requires original data, synthesis of multiple sources, and original interpretation and argumentation before providing an answer. 

Steps for developing a good research question

The importance of research questions cannot be understated. When drafting a research question, use the following frameworks to guide the components of your question to ease the process. 4  

• Determine the requirements: Before constructing a good research question, set your research requirements. What is the purpose? Is it descriptive, comparative, or explorative research? Determining the research aim will help you choose the most appropriate topic and word your question appropriately. 
• Select a broad research topic: Identify a broader subject area of interest that requires investigation. Techniques such as brainstorming or concept mapping can help identify relevant connections and themes within a broad research topic. For example, how to learn and help students learn. 
• Perform preliminary investigation: Preliminary research is needed to obtain up-to-date and relevant knowledge on your topic. It also helps identify issues currently being discussed from which information gaps can be identified. 
• Narrow your focus: Narrow the scope and focus of your research to a specific niche. This involves focusing on gaps in existing knowledge or recent literature or extending or complementing the findings of existing literature. Another approach involves constructing strong research questions that challenge your views or knowledge of the area of study (Example: Is learning consistent with the existing learning theory and research). 
• Identify the research problem: Once the research question has been framed, one should evaluate it. This is to realize the importance of the research questions and if there is a need for more revising (Example: How do your beliefs on learning theory and research impact your instructional practices). 

How to write a research question

Those struggling to understand how to write a research question, these simple steps can help you simplify the process of writing a research question. 

Sample Research Questions

The following are some bad and good research question examples 

• Example 1 

• Example 2 

References:  

• Thabane, L., Thomas, T., Ye, C., & Paul, J. (2009). Posing the research question: not so simple.  Canadian Journal of Anesthesia/Journal canadien d’anesthésie ,  56 (1), 71-79. 
• Rutberg, S., & Bouikidis, C. D. (2018). Focusing on the fundamentals: A simplistic differentiation between qualitative and quantitative research.  Nephrology Nursing Journal ,  45 (2), 209-213. 
• Kyngäs, H. (2020). Qualitative research and content analysis.  The application of content analysis in nursing science research , 3-11. 
• Mattick, K., Johnston, J., & de la Croix, A. (2018). How to… write a good research question.  The clinical teacher ,  15 (2), 104-108. 
• Fandino, W. (2019). Formulating a good research question: Pearls and pitfalls.  Indian Journal of Anaesthesia ,  63 (8), 611. 
• Richardson, W. S., Wilson, M. C., Nishikawa, J., & Hayward, R. S. (1995). The well-built clinical question: a key to evidence-based decisions.  ACP journal club ,  123 (3), A12-A13 

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

Research Methodology Example

Detailed Walkthrough + Free Methodology Chapter Template

If you’re working on a dissertation or thesis and are looking for an example of a research methodology chapter , you’ve come to the right place.

In this video, we walk you through a research methodology from a dissertation that earned full distinction , step by step. We start off by discussing the core components of a research methodology by unpacking our free methodology chapter template . We then progress to the sample research methodology to show how these concepts are applied in an actual dissertation, thesis or research project.

If you’re currently working on your research methodology chapter, you may also find the following resources useful:

• Research methodology 101 : an introductory video discussing what a methodology is and the role it plays within a dissertation
• Research design 101 : an overview of the most common research designs for both qualitative and quantitative studies
• Variables 101 : an introductory video covering the different types of variables that exist within research.
• Sampling 101 : an overview of the main sampling methods
• Methodology tips : a video discussion covering various tips to help you write a high-quality methodology chapter
• Private coaching : Get hands-on help with your research methodology

PS – If you’re working on a dissertation, be sure to also check out our collection of dissertation and thesis examples here .

FAQ: Research Methodology Example

Research methodology example: frequently asked questions, is the sample research methodology real.

Yes. The chapter example is an extract from a Master’s-level dissertation for an MBA program. A few minor edits have been made to protect the privacy of the sponsoring organisation, but these have no material impact on the research methodology.

Can I replicate this methodology for my dissertation?

As we discuss in the video, every research methodology will be different, depending on the research aims, objectives and research questions. Therefore, you’ll need to tailor your literature review to suit your specific context.

You can learn more about the basics of writing a research methodology chapter here .

Where can I find more examples of research methodologies?

The best place to find more examples of methodology chapters would be within dissertation/thesis databases. These databases include dissertations, theses and research projects that have successfully passed the assessment criteria for the respective university, meaning that you have at least some sort of quality assurance.

The Open Access Thesis Database (OATD) is a good starting point.

How do I get the research methodology chapter template?

You can access our free methodology chapter template here .

Is the methodology template really free?

Yes. There is no cost for the template and you are free to use it as you wish.

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How to Write a Research Methodology for a Research Paper

Crafting a comprehensive research paper can be daunting. Understanding diverse citation styles and various subject areas presents a challenge for many.

Without clear examples, students often feel lost and overwhelmed, unsure of how to start or which style fits their subject.

Explore our collection of expertly written research paper examples. We’ve covered various citation styles and a diverse range of subjects.

So, read on!

• 1. Research Paper Example for Different Formats
• 2. Examples for Different Research Paper Parts
• 3. Research Paper Examples for Different Fields
• 4. Research Paper Example Outline

Research Paper Example for Different Formats

Following a specific formatting style is essential while writing a research paper . Knowing the conventions and guidelines for each format can help you in creating a perfect paper. Here we have gathered examples of research paper for most commonly applied citation styles :

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APA (American Psychological Association) style is commonly used in social sciences, psychology, and education. This format is recognized for its clear and concise writing, emphasis on proper citations, and orderly presentation of ideas.

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MLA (Modern Language Association) style is frequently employed in humanities disciplines, including literature, languages, and cultural studies. An MLA research paper might explore literature analysis, linguistic studies, or historical research within the humanities. 

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Research Paper Example Chicago

Chicago style is utilized in various fields like history, arts, and social sciences. Research papers in Chicago style could delve into historical events, artistic analyses, or social science inquiries. 

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Research Paper Example Harvard

Harvard style is widely used in business, management, and some social sciences. Research papers in Harvard style might address business strategies, case studies, or social policies.

View this sample Harvard style paper here:

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Examples for Different Research Paper Parts

A research paper has different parts. Each part is important for the overall success of the paper. Chapters in a research paper must be written correctly, using a certain format and structure.

The following are examples of how different sections of the research paper can be written.

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The research proposal acts as a detailed plan or roadmap for your study, outlining the focus of your research and its significance. It's essential as it not only guides your research but also persuades others about the value of your study.

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An abstract serves as a concise overview of your entire research paper. It provides a quick insight into the main elements of your study. It summarizes your research's purpose, methods, findings, and conclusions in a brief format.

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A literature review summarizes the existing research on your study's topic, showcasing what has already been explored. This section adds credibility to your own research by analyzing and summarizing prior studies related to your topic.

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Methodology

The methodology section functions as a detailed explanation of how you conducted your research. This part covers the tools, techniques, and steps used to collect and analyze data for your study.

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The Effects of Food Deprivation on Concentration and Perseverance

Art History Research Paper Sample

Studying art history includes examining artworks, understanding their historical context, and learning about the artists. This helps analyze and interpret how art has evolved over various periods and regions.

Check out this sample paper analyzing European art and impacts:

European Art History: A Primer

Research Paper Example Outline

Before you plan on writing a well-researched paper, make a rough draft. An outline can be a great help when it comes to organizing vast amounts of research material for your paper.

Here is an outline of a research paper example:

Here is a downloadable sample of a standard research paper outline:

Research Paper Outline

Want to create the perfect outline for your paper? Check out this in-depth guide on creating a research paper outline for a structured paper!

Good Research Paper Examples for Students

Here are some more samples of research paper for students to learn from:

Fiscal Research Center - Action Plan

Qualitative Research Paper Example

Research Paper Example Introduction

How to Write a Research Paper Example

Research Paper Example for High School

Now that you have explored the research paper examples, you can start working on your research project. Hopefully, these examples will help you understand the writing process for a research paper.

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Home » Research Findings – Types Examples and Writing Guide

Research Findings – Types Examples and Writing Guide

Table of Contents

Research Findings

Definition:

Research findings refer to the results obtained from a study or investigation conducted through a systematic and scientific approach. These findings are the outcomes of the data analysis, interpretation, and evaluation carried out during the research process.

Types of Research Findings

There are two main types of research findings:

Qualitative Findings

Qualitative research is an exploratory research method used to understand the complexities of human behavior and experiences. Qualitative findings are non-numerical and descriptive data that describe the meaning and interpretation of the data collected. Examples of qualitative findings include quotes from participants, themes that emerge from the data, and descriptions of experiences and phenomena.

Quantitative Findings

Quantitative research is a research method that uses numerical data and statistical analysis to measure and quantify a phenomenon or behavior. Quantitative findings include numerical data such as mean, median, and mode, as well as statistical analyses such as t-tests, ANOVA, and regression analysis. These findings are often presented in tables, graphs, or charts.

Both qualitative and quantitative findings are important in research and can provide different insights into a research question or problem. Combining both types of findings can provide a more comprehensive understanding of a phenomenon and improve the validity and reliability of research results.

Parts of Research Findings

Research findings typically consist of several parts, including:

• Introduction: This section provides an overview of the research topic and the purpose of the study.
• Literature Review: This section summarizes previous research studies and findings that are relevant to the current study.
• Methodology : This section describes the research design, methods, and procedures used in the study, including details on the sample, data collection, and data analysis.
• Results : This section presents the findings of the study, including statistical analyses and data visualizations.
• Discussion : This section interprets the results and explains what they mean in relation to the research question(s) and hypotheses. It may also compare and contrast the current findings with previous research studies and explore any implications or limitations of the study.
• Conclusion : This section provides a summary of the key findings and the main conclusions of the study.
• Recommendations: This section suggests areas for further research and potential applications or implications of the study’s findings.

How to Write Research Findings

Writing research findings requires careful planning and attention to detail. Here are some general steps to follow when writing research findings:

• Organize your findings: Before you begin writing, it’s essential to organize your findings logically. Consider creating an outline or a flowchart that outlines the main points you want to make and how they relate to one another.
• Use clear and concise language : When presenting your findings, be sure to use clear and concise language that is easy to understand. Avoid using jargon or technical terms unless they are necessary to convey your meaning.
• Use visual aids : Visual aids such as tables, charts, and graphs can be helpful in presenting your findings. Be sure to label and title your visual aids clearly, and make sure they are easy to read.
• Use headings and subheadings: Using headings and subheadings can help organize your findings and make them easier to read. Make sure your headings and subheadings are clear and descriptive.
• Interpret your findings : When presenting your findings, it’s important to provide some interpretation of what the results mean. This can include discussing how your findings relate to the existing literature, identifying any limitations of your study, and suggesting areas for future research.
• Be precise and accurate : When presenting your findings, be sure to use precise and accurate language. Avoid making generalizations or overstatements and be careful not to misrepresent your data.
• Edit and revise: Once you have written your research findings, be sure to edit and revise them carefully. Check for grammar and spelling errors, make sure your formatting is consistent, and ensure that your writing is clear and concise.

Research Findings Example

Following is a Research Findings Example sample for students:

Title: The Effects of Exercise on Mental Health

Sample : 500 participants, both men and women, between the ages of 18-45.

Methodology : Participants were divided into two groups. The first group engaged in 30 minutes of moderate intensity exercise five times a week for eight weeks. The second group did not exercise during the study period. Participants in both groups completed a questionnaire that assessed their mental health before and after the study period.

Findings : The group that engaged in regular exercise reported a significant improvement in mental health compared to the control group. Specifically, they reported lower levels of anxiety and depression, improved mood, and increased self-esteem.

Conclusion : Regular exercise can have a positive impact on mental health and may be an effective intervention for individuals experiencing symptoms of anxiety or depression.

Applications of Research Findings

Research findings can be applied in various fields to improve processes, products, services, and outcomes. Here are some examples:

• Healthcare : Research findings in medicine and healthcare can be applied to improve patient outcomes, reduce morbidity and mortality rates, and develop new treatments for various diseases.
• Education : Research findings in education can be used to develop effective teaching methods, improve learning outcomes, and design new educational programs.
• Technology : Research findings in technology can be applied to develop new products, improve existing products, and enhance user experiences.
• Business : Research findings in business can be applied to develop new strategies, improve operations, and increase profitability.
• Public Policy: Research findings can be used to inform public policy decisions on issues such as environmental protection, social welfare, and economic development.
• Social Sciences: Research findings in social sciences can be used to improve understanding of human behavior and social phenomena, inform public policy decisions, and develop interventions to address social issues.
• Agriculture: Research findings in agriculture can be applied to improve crop yields, develop new farming techniques, and enhance food security.
• Sports : Research findings in sports can be applied to improve athlete performance, reduce injuries, and develop new training programs.

When to use Research Findings

Research findings can be used in a variety of situations, depending on the context and the purpose. Here are some examples of when research findings may be useful:

• Decision-making : Research findings can be used to inform decisions in various fields, such as business, education, healthcare, and public policy. For example, a business may use market research findings to make decisions about new product development or marketing strategies.
• Problem-solving : Research findings can be used to solve problems or challenges in various fields, such as healthcare, engineering, and social sciences. For example, medical researchers may use findings from clinical trials to develop new treatments for diseases.
• Policy development : Research findings can be used to inform the development of policies in various fields, such as environmental protection, social welfare, and economic development. For example, policymakers may use research findings to develop policies aimed at reducing greenhouse gas emissions.
• Program evaluation: Research findings can be used to evaluate the effectiveness of programs or interventions in various fields, such as education, healthcare, and social services. For example, educational researchers may use findings from evaluations of educational programs to improve teaching and learning outcomes.
• Innovation: Research findings can be used to inspire or guide innovation in various fields, such as technology and engineering. For example, engineers may use research findings on materials science to develop new and innovative products.

Purpose of Research Findings

The purpose of research findings is to contribute to the knowledge and understanding of a particular topic or issue. Research findings are the result of a systematic and rigorous investigation of a research question or hypothesis, using appropriate research methods and techniques.

The main purposes of research findings are:

• To generate new knowledge : Research findings contribute to the body of knowledge on a particular topic, by adding new information, insights, and understanding to the existing knowledge base.
• To test hypotheses or theories : Research findings can be used to test hypotheses or theories that have been proposed in a particular field or discipline. This helps to determine the validity and reliability of the hypotheses or theories, and to refine or develop new ones.
• To inform practice: Research findings can be used to inform practice in various fields, such as healthcare, education, and business. By identifying best practices and evidence-based interventions, research findings can help practitioners to make informed decisions and improve outcomes.
• To identify gaps in knowledge: Research findings can help to identify gaps in knowledge and understanding of a particular topic, which can then be addressed by further research.
• To contribute to policy development: Research findings can be used to inform policy development in various fields, such as environmental protection, social welfare, and economic development. By providing evidence-based recommendations, research findings can help policymakers to develop effective policies that address societal challenges.

Characteristics of Research Findings

Research findings have several key characteristics that distinguish them from other types of information or knowledge. Here are some of the main characteristics of research findings:

• Objective : Research findings are based on a systematic and rigorous investigation of a research question or hypothesis, using appropriate research methods and techniques. As such, they are generally considered to be more objective and reliable than other types of information.
• Empirical : Research findings are based on empirical evidence, which means that they are derived from observations or measurements of the real world. This gives them a high degree of credibility and validity.
• Generalizable : Research findings are often intended to be generalizable to a larger population or context beyond the specific study. This means that the findings can be applied to other situations or populations with similar characteristics.
• Transparent : Research findings are typically reported in a transparent manner, with a clear description of the research methods and data analysis techniques used. This allows others to assess the credibility and reliability of the findings.
• Peer-reviewed: Research findings are often subject to a rigorous peer-review process, in which experts in the field review the research methods, data analysis, and conclusions of the study. This helps to ensure the validity and reliability of the findings.
• Reproducible : Research findings are often designed to be reproducible, meaning that other researchers can replicate the study using the same methods and obtain similar results. This helps to ensure the validity and reliability of the findings.

Advantages of Research Findings

Research findings have many advantages, which make them valuable sources of knowledge and information. Here are some of the main advantages of research findings:

• Evidence-based: Research findings are based on empirical evidence, which means that they are grounded in data and observations from the real world. This makes them a reliable and credible source of information.
• Inform decision-making: Research findings can be used to inform decision-making in various fields, such as healthcare, education, and business. By identifying best practices and evidence-based interventions, research findings can help practitioners and policymakers to make informed decisions and improve outcomes.
• Identify gaps in knowledge: Research findings can help to identify gaps in knowledge and understanding of a particular topic, which can then be addressed by further research. This contributes to the ongoing development of knowledge in various fields.
• Improve outcomes : Research findings can be used to develop and implement evidence-based practices and interventions, which have been shown to improve outcomes in various fields, such as healthcare, education, and social services.
• Foster innovation: Research findings can inspire or guide innovation in various fields, such as technology and engineering. By providing new information and understanding of a particular topic, research findings can stimulate new ideas and approaches to problem-solving.
• Enhance credibility: Research findings are generally considered to be more credible and reliable than other types of information, as they are based on rigorous research methods and are subject to peer-review processes.

Limitations of Research Findings

While research findings have many advantages, they also have some limitations. Here are some of the main limitations of research findings:

• Limited scope: Research findings are typically based on a particular study or set of studies, which may have a limited scope or focus. This means that they may not be applicable to other contexts or populations.
• Potential for bias : Research findings can be influenced by various sources of bias, such as researcher bias, selection bias, or measurement bias. This can affect the validity and reliability of the findings.
• Ethical considerations: Research findings can raise ethical considerations, particularly in studies involving human subjects. Researchers must ensure that their studies are conducted in an ethical and responsible manner, with appropriate measures to protect the welfare and privacy of participants.
• Time and resource constraints : Research studies can be time-consuming and require significant resources, which can limit the number and scope of studies that are conducted. This can lead to gaps in knowledge or a lack of research on certain topics.
• Complexity: Some research findings can be complex and difficult to interpret, particularly in fields such as science or medicine. This can make it challenging for practitioners and policymakers to apply the findings to their work.
• Lack of generalizability : While research findings are intended to be generalizable to larger populations or contexts, there may be factors that limit their generalizability. For example, cultural or environmental factors may influence how a particular intervention or treatment works in different populations or contexts.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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References provide the information necessary for readers to identify and retrieve each work cited in the text .

Check each reference carefully against the original publication to ensure information is accurate and complete. Accurately prepared references help establish your credibility as a careful researcher and writer.

Consistency in reference formatting allows readers to focus on the content of your reference list, discerning both the types of works you consulted and the important reference elements (who, when, what, and where) with ease. When you present each reference in a consistent fashion, readers do not need to spend time determining how you organized the information. And when searching the literature yourself, you also save time and effort when reading reference lists in the works of others that are written in APA Style.

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Poster Samples

Looking at samples of real student posters can help you generate ideas and define your goals. As you get started, it may be helpful to look at examples of finished posters.

Below are a number of sample posters created by UT undergraduates. There is a brief discussion of each poster highlighting its greatest strengths and areas where there is room for improvement.

• More than one type of visual aid
• Logical order for sections
• Acknowledgments

Room for improvement

• Background may be distracting, or detract from content
• Sections and images are not aligned
• Too many visual components clutter poster

• White space
• Legible text and graphics
• Reports preliminary results
• All participants listed as authors, with affiliations provided
• Lacks Citations and Acknowledgements
• Labeling of images/graphics
• Inconsistent text alignment
• Color-saturated background

• Clearly defined research questions
• Effective use of visual aids
• Clear organizational structure
• Bullets break up text
• Technical language/undefined acronyms (accessible to limited audience)
• Narrow margins within text boxes
• Too many thick borders around boxes
• Uses UT seal instead of college or university wordmark

• Clear introductory material
• Use of bullet points
• Logical flow
• Color-coding in graphics
• Lacks references section
• May not be accessible to all audiences (some technical language)
• No need for borders around sections (the blue headers are sufficient)

• Compelling visual aids
• Strategic use of color
• Clear sections
• Inconsistent fonts in body text
• Abstract section mislabeled
• Bullet points are great, but only if they’re used judiciously

• Parameters of study well defined
• Clearly defined research question
• Simple color scheme
• Use of white space
• Discussion of Results
• Minor formatting misalignments
• Unauthorized use of UT seal (use wordmark instead)

• Venn diagram in discussion
• Consistent graphics
• Multiple types of visual aids
• Light text on dark background
• Color backgrounds should be avoided, especially dark ones
• Unlabeled, non-credited photos

• Easy to read
• Use of shapes, figures, and bullets to break up text
• Compelling title (and title font size)
• Clean overall visual impression
• Many sections without a clear flow between them
• Lacks acknowledgements

• Use of images/graphics
• Clear title
• Accessible but professional tone
• Length/density of text blocks
• Tiny photo citations
• Connections between images and descriptive text
• Vertical boxes unnecessary

• Compelling title
• Font sizes throughout (hierarchy of text)
• Simple graphics
• Lacks clear Background section
• Relationship of Findings and Conclusion to Research questions

• Use of visual aids
• Uneven column width
• Center-justfied body text
• Lacks “Methods” section

• Use of bullets
• Too many different font styles (serif and sans serif, bold and normal)
• Concise interpretation of graphics

• Accessible visual structure
• Clear, simple graphics
• Fonts and font sizes
• Analysis of graphic data
• Discussion of significance
• Lacks author’s affiliation and contact information

• Balance among visuals, text and white space
• Data presented in visual format (SmartArt)
• Accesible to many audiences (simple enough for general audience, but enough methodological detail for experts)
• Some more editing needed
• When targeting an expert audience (as in the methodology section), should also report statistics ( r, p, t, F, etc.)

• Large, clear title
• Creative adaptation of sections
• Use of lists (rather than paragraphs)
• Accessible to diverse audience
• Connection between visuals (sheet music) and content

• Strategic use of color for section headers
• Labeling and citation of images
• Accessible to a broad audience
• Wide margins around poster edges
• Slightly text-heavy
• Data referenced (“Methodology”) but not discussed

What is my next step?

Begin working on the content for your poster at Create Your Message .

• Master of Quantitative Finance
• Master of Professional Accountancy
• Master of Science in Business Analytics
• Flex Evening & Executive MBA
• Full-Time MBA
• Business Analytics
• Entrepreneurship
• Marketing/Sales
• Product Management
• Supply Chain Management
• Global Opportunities
• Self Assessment & Career Strategy
• Market Research
• Narrative & Personal Branding
• Resume & Cover Letters
• Interviewing
• Job & Internship Search
• Offer Assessment & Negotiation
• Career Coaches
• Employer Engagement
• RSA & Student Clubs

How to Write an Application Letter (Sample Included!)

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How to Write an Application Letter (Sample Included!) was originally published on The Muse , a great place to research companies and careers. Click here to search for great jobs and companies near you.

Whether you’re applying for a job , internship , scholarship, or volunteer position, a well-crafted application letter can help you stand out. It’s your chance to introduce yourself and make a strong first impression that sets you apart from the competition.

But how do you write an application letter that’s effective? Below, we’ll explain when to use this method of introduction and give you practical tips on writing one that gets results. Plus, we’ve included a sample application letter and a template to help you create the perfect document for any opportunity.

Apply for the role of your dreams! One of these open jobs on The Muse could be the perfect fit »

What is an application letter?

An application letter is a document sent with your resume to provide additional information on your skills and experience. It’s a crucial part of an application for work as it introduces you to potential employers and highlights your qualifications.

While some companies request it at the beginning of the application process, others might ask for it later, or not at all—but it’s always a valuable addition.

Unlike a resume, which outlines your work history, a written application allows you to elaborate on your achievements and how they relate to the job you are applying for. It is a much more specific way to introduce yourself and explain why you would be a good fit for the job.

How is an application letter different from a cover letter?

Some people use the terms “application letter” and “cover letter” interchangeably, but there are subtle differences between the two.

An application letter serves as your formal introduction to a potential employer. It highlights your interest in the role, your qualifications, and why you’re a good fit for the position. It’s a standalone document that provides a comprehensive overview of your skills and experiences.

On the other hand, a cover letter is usually more concise than an application letter and serves as a complementary document to your resume, providing additional context to your job application. It elaborates on specific points from your resume and explains how your background aligns with the job requirements.

Also, job application letters follow a more formal structure, often resembling a traditional business letter. They include your contact information, the date, and the employer’s contact information at the top. An application letter is usually addressed to a specific individual, such as the hiring manager or recruiter. While cover letters also have a professional tone, they can be less formal in structure.

Finally, the application letter is used primarily for job applications, internship applications, scholarship applications, and volunteer positions. In contrast, the cover letter is specifically used to accompany a resume during job applications.

When do you need to send an application letter?

Application letters are typically required when applying for jobs. However, there are other scenarios where you might need one:

• Scholarship applications: When applying for scholarships, this kind of letter can help you stand out by showcasing your academic achievements and career goals .
• Volunteer positions: Some volunteer organizations require an application letter to understand your motivations and skills relevant to the position.
• Internship applications: Internships often require this document to understand your interest in the role and what you hope to gain from the experience.
• Networking purposes: Sending one when reaching out to potential mentors or industry professionals can help you establish a connection and explain your career aspirations.

7 tips on how to write a job application letter

Writing an effective application letter involves more than just summarizing your resume. Here are seven tips to write yours:

1. Research the company—at least do a quick Google search!

Before you start writing, research the company to understand its culture, values, and needs. Tailor your letter to align with the company’s mission and the job description. There is nothing better for an HR professional than feeling that you don’t just want any job; you want to work with them for specific reasons, such as X and Y.

“Address the letter to the hiring manager by name if possible,” says Mike Chappell, CEO of FormsPal , who has more than a decade of experience reviewing application letters. “This shows that you’ve done your research and are genuinely interested in the company.”

2. Use a professional format and design

Your application letter should follow a formal letter of application format. Use a standard font like Times New Roman or Arial, and keep the font size between 10 and 12 points. Include your contact information, the date, and the employer’s contact information at the top of the letter.

There are many layouts online that you can use. Find one that represents your style and complements your resume.

3. Make it engaging from the start with a strong opening

Your opening paragraph should grab the reader’s attention. Mention the position you’re applying for and where you found the job listing. If you were referred by someone, include their name. Briefly introduce yourself and explain why you’re interested in the role.

4. Highlight your qualifications—what you can’t fully convey in your resume

In the body of your applicant letter, highlight your relevant skills, experiences, and achievements. “Use specific examples to showcase your accomplishments and how they relate to the job you’re applying for,” Chappell says. “ Quantifiable results can make a strong impact.”

Avoid repeating information from your resume; instead, expand on your most relevant experiences.

5. Show enthusiasm and genuine interest

Employers want to hire candidates who are enthusiastic about the role and the company. Show your excitement for the opportunity. Explain why you are specifically interested in this job and how it aligns with your career goals.

6. Keep it concise

While it’s important to provide enough detail, your application letter should be concise. Aim for one page, with three to four paragraphs. Be clear and to the point, avoiding unnecessary fluff.

7. Proofread carefully

Typos and grammatical errors can leave a negative impression on employers. Carefully proofread your letter before sending it. Consider asking another person to review it as well.

Letter of application sample

Here’s a super complete example of application letter to help you get started:

August 1, 2024

Ms. Jane Doe

Hiring Manager

Innovative Solutions Inc.

456 Maple Avenue

Springfield, IL 62705

Dear Ms. Doe,

I am writing to express my interest in the Marketing Manager position at Innovative Solutions Inc., as advertised on your company’s careers page. With more than five years of experience in marketing and a proven track record of successful campaigns, I am excited about the opportunity to contribute to your team and drive impactful marketing strategies.

In my previous role as a Senior Marketing Specialist at Creative Solutions LLC, I led a team in developing and executing a comprehensive marketing strategy that resulted in a 30% increase in brand awareness and a 25% boost in lead generation. My responsibilities included overseeing digital marketing campaigns, analyzing market trends, and coordinating with cross-functional teams to ensure alignment with overall business goals. This experience has honed my skills in strategic planning, data analysis, and team leadership.

I am particularly impressed by Innovative Solutions Inc.’s commitment to leveraging cutting-edge technology to deliver innovative marketing solutions. Your recent campaign, which utilized artificial intelligence to optimize ad targeting, is a testament to your forward-thinking approach. I am eager to bring my expertise in digital marketing and campaign management to your team and contribute to similar groundbreaking projects.

My strong analytical skills, combined with my ability to lead and inspire a team, make me a great fit for this role. I am confident that my background and enthusiasm for innovative marketing strategies align well with the needs of Innovative Solutions Inc.

Thank you for considering my application. I look forward to the opportunity to discuss how my skills and experiences can contribute to the continued success of Innovative Solutions Inc.

123 Elm Street

Springfield, IL 62704

[email protected]

(555) 123-4567

Template for an application letter

You can also use the following application format to structure your application letter for a job:

[Recipient’s name]

[Company’s name]

[Company’s address]

[City, State, ZIP Code]

Dear [Recipient’s name],

I am writing to express my interest in the [Job title] position at [Company name] as advertised on [Where you found the job listing]. With my background in [Field or industry] and a passion for [Specific aspect of the job or industry], I am excited about the opportunity to contribute to your team.

In my previous role at [Previous company], I developed [Specific skills or achievements]. I successfully [Describe a project or responsibility], which resulted in [Quantifiable result or achievement]. This experience has equipped me with [Relevant skills] that I am eager to bring to [Company name].

I am particularly impressed by [Company name]’s commitment to [Specific company initiative or value], and I am enthusiastic about the prospect of working with a team that values [Related value or skill]. I am confident that my skills and experiences align well with the requirements of the [Job title] position.

Thank you for considering my application. I look forward to the opportunity to discuss how my background, skills, and enthusiasm can contribute to the success of [Company Name].

[Your Name]

[Your address]

[Your email address]

[Your phone number]

Common mistakes to avoid

When writing a letter of application for employment, be aware of these common mistakes:

• Being too generic: Focus your letter on the specific job and company, and mention detailed information about them. Don’t default to a one-size-fits-all approach or AI-written document. “It is generally best to avoid using generative AI to write your application letters for you,” says Edward Tian, CEO of AI detector GPTZero . “Only you can write about those specific aspects of your identity and experiences in such a personal way.”
• Focusing too much on yourself: While it’s important to highlight your qualifications, make sure to explain how you can benefit the company. “You can talk about your career goals, college classes that piqued your interest in the type of job you’re applying to—just make sure that they tie into why they make you uniquely qualified or well-positioned for the job,” Tian says.
• Including irrelevant information: Avoid discussing unrelated jobs or hobbies, for example.
• Using a casual tone: Maintain a professional tone throughout your letter. Avoid slang or overly casual language.

Need a bit more guidance in your job search? Read this next: How to Apply for a Job Online: 10 Tips to Stand Out and Land an Interview

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Professional Letter of Recommendation: Sample, Format & Examples

• Last Updated On August 22, 2024
• Published In General

A professional letter of recommendation can be a crucial element in your application, helping you stand out in a crowded field. Schools like MIT , for example, require two letters of recommendation as part of their admissions process.  

Table of Content

These letters, typically written by professors or supervisors, strongly endorse your skills, character, and potential. Admissions committees rely on these insights to make informed decisions. 

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In this article, you’ll learn how to craft a compelling professional letter of recommendation to help you take the next step in your career or academic journey. Dive in!

Here’s everything you will learn in greater detail in this blog about professional letter of recommendation.

What is a Professional Letter of Recommendation?

A professional letter of recommendation, often called a LOR, is vital to many application processes, whether for academic programs, jobs, or scholarships. It provides a trusted perspective on your abilities, character, and potential. 

Universities such as Harvard and Stanford often require two to three letters of recommendation as part of their application process. These letters offer admissions committees a deeper understanding of who you are beyond your grades or resume.

Writing an impactful LOR can be challenging, so having a well-crafted example can be incredibly helpful. By reviewing a solid sample, you can learn how to showcase your strengths and experiences effectively, helping you make a lasting impression.

How to Write a Professional Letter of Recommendation?

Writing a professional letter of recommendation involves presenting a clear and compelling endorsement of the candidate’s qualifications. 

In this section, you’ll learn the key steps to structure your letter effectively, including what information to include and how to highlight your strengths. 

Later in the blog, you will also find professional reference letter templates and learn how to ensure your letter strongly impacts the reader.

Professional Letter of Recommendation: Structure

Getting into a prestigious MBA or PhD program is a challenging feat. One of the most critical components of your application is the strength of your Letters of Recommendation (LORs). 

Schools like Caltech typically ask for three LORs, favouring those from academic mentors who can speak to your research abilities and potential.

These letters are vital to your application, offering essential external validation of your qualifications.

Here is a quick overview of the structure of professional reference letter templates.

Professional Letter of Recommendation Format

As you focus on your IELTS preparation and other application tasks, paying attention to a solid professional letter of recommendation is crucial. A well-crafted and structured LOR can significantly impact your chances of admission, making it a key element in your college application.

Here is a professional letter of recommendation format.

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Professional letter of recommendation examples.

A sample professional reference letter can help you craft a solid recommendation. However, using these examples as a guide rather than copying them directly is essential.

Below, you’ll find professional letter of recommendation examples. These professional reference letter templates show how your supervisors can highlight your qualifications and suitability for higher studies.

Please see a sample professional reference letter and a professional letter of recommendation for ms below.

DISCLAIMER: The name “John Smith” is used in this sample LOR for illustrative purposes only. 

Sample Professional Reference Letter

[Full Name] Research Scientist [Company Name] [Company Address] [City, State ZIP Code] [Email Address] [Phone Number] [Date]

Dear Admissions Committee,

I am pleased to write this letter of recommendation for John Smith, who has been an outstanding member of our research team at [Company Name] for the past three years. Throughout this time, I have had the privilege of supervising John closely, observing his impressive intellectual capabilities, unwavering dedication, and exceptional problem-solving skills.

As a research scientist, John has consistently exceeded expectations. His contributions, particularly in [specific research area], have been critical to our team’s success. For example, his leadership in the [project name] initiative was vital to achieving [specific outcome]. John demonstrated a deep understanding of the challenges involved and developed innovative solutions that significantly advanced our research objectives. His ability to navigate complex problems and deliver effective solutions has set him apart as a critical contributor to our team’s accomplishments.

John’s standout qualities are his ability to combine theoretical knowledge with practical application seamlessly. His work on [specific project or task] is a perfect example. By [briefly describing particular actions taken], John achieved [quantifiable result], showcasing his analytical skills and talent for turning complex concepts into real-world outcomes. This project highlighted his technical proficiency and ability to think critically and apply his knowledge in ways that yield tangible results.

Beyond his technical expertise, John excels in interpersonal and communication skills. He is a collaborative team member who freely shares his knowledge with colleagues, ensuring everyone benefits from his insights. His ability to explain complex ideas clearly and understandably has been invaluable in both internal discussions and external presentations. Additionally, John has taken on leadership roles within the team, mentoring junior researchers and contributing to a positive work environment. His leadership has helped foster a collaborative and innovative atmosphere crucial to our collective success.

John’s passion for research and drive for continuous learning are truly admirable. He is always seeking new challenges and opportunities for growth. For instance, [describe a specific example of initiative or self-directed learning] demonstrates his intellectual curiosity and commitment to professional development. This proactive approach to learning and growth is a testament to his dedication to his field and his desire to improve and expand his expertise continually.

I am confident that John possesses the intellectual capacity, technical expertise, and personal qualities necessary to excel in a Master’s program. His strong foundation in [specific field] and his enthusiasm for research make him an excellent candidate for advanced studies. I highly recommend John Smith for admission to your program, as he will be a valuable addition to your research community. Please feel free to contact me if you need any further information.

Sincerely, [Full Name] Manager – Sales [Company Name]

Professional Letter of Recommendation for MS

I am pleased to recommend John Smith, who has been an exceptional member of our research team at [Company Name] for the past three years. During this period, I have had the privilege of supervising John directly, allowing me to observe his impressive intellectual abilities, dedication, and exceptional problem-solving skills daily.

John has consistently delivered outstanding work as a research scientist. His contributions, particularly in [specific research area], have been pivotal to our team’s success. For example, his leadership in the [project name] initiative was crucial in achieving [specific outcome]. John’s ability to deeply understand the challenges associated with this project and his innovative approach to overcoming them significantly advanced our research efforts. His contributions went beyond what was expected, demonstrating his technical prowess and his commitment to excellence.

One of John’s greatest strengths is his ability to bridge theoretical knowledge with practical application. This was evident in his work on [specific project or task]. By [briefly describing particular actions taken], John achieved [quantifiable result], effectively showcasing his strong analytical skills and remarkable ability to turn complex concepts into tangible, real-world results. His work did not just meet the project’s objectives; it set a new standard for what could be achieved within our team, earning him the respect and admiration of his colleagues.

In addition to his technical expertise, John possesses excellent interpersonal and communication skills. He is a collaborative team player who readily shares his knowledge with colleagues, often going out of his way to ensure that others understand the intricate details of complex projects. His clear and concise communication has been invaluable, whether in internal discussions or during external presentations, and his ability to articulate complex ideas understandably has contributed significantly to the success of our projects. Furthermore, John has demonstrated strong leadership abilities, taking on roles where he has mentored junior researchers, helping them grow and develop their skills. 

John’s passion for research and commitment to continuous learning are commendable. He is always seeking new challenges and opportunities for growth, for instance, [describe a specific example of initiative or self-directed learning], which is a testament to his intellectual curiosity and dedication to professional development.

I do not doubt that John possesses the intellectual capacity, technical skills, and personal qualities necessary to excel in a master’s program. His strong background in [specific field] and enthusiasm for work make him an ideal candidate for advanced studies. I wholeheartedly recommend John Smith for admission to your program and am confident he will be a valuable asset to your academic community. If you require any further information, please do not hesitate to contact me.

Sincerely, [Full Name] Senior Engineer [Company Name]

Vocabulary for Writing a Professional Letter of Recommendation

Crafting a compelling professional letter of recommendation involves more than just structure; your chosen language is crucial in shaping how the admissions committee views your application.

Below, you’ll find some suggested vocabulary to help strengthen your LOR and make it more impactful.

Keep in mind that these words are meant to enhance your writing. Thoughtful use of them will improve the professionalism and effectiveness of your recommendation.

Tips to Write A Better Professional Letter of Recommendation 

Did you know that in 2024, over 1.3 million Indian students went abroad for higher studies? If you’re aiming for admission to top universities like Oxford in the UK or Harvard in the US, having a solid professional letter of recommendation for graduate school is essential. 

These letters must be thoughtfully written to ensure your application stands out and increases your chances of being selected.

Below are the crucial tips for writing a compelling professional letter of recommendation for graduate school.

• Choose recommenders who understand your graduate program’s requirements and can effectively highlight your strengths.
• Maintain regular contact with your recommenders, sharing your research goals and achievements to provide them with plenty of information.
• Encourage each recommender to focus on different aspects of your qualifications to create a well-rounded picture.
• Ensure online recommendation forms are submitted before the application deadline to avoid last-minute stress.
• Emphasise the importance of honest and detailed information in the LOR, avoiding exaggeration or false claims.
• Establish the relationship between you and the recommender within the letter.
• Showcase your unique qualities, abilities, and potential for success in the graduate program.
• Encourage recommenders to write personalised letters reflecting your achievements rather than relying on generic templates.

Whom Should You Ask for a Professional Letter of Recommendation?

Choosing the right person for your professional letter of recommendation is crucial. This is especially true in today’s competitive environment, where 25% of the one million international students in the US are Indian.

Your recommender should be someone who can genuinely advocate for you and provide an objective assessment of your abilities. A solid professional letter of recommendation offers a unique perspective, reflecting the recommender’s observations and experiences with you helping your application stand out.

Your ideal recommender should be someone who:

• Has worked closely with you.
• Understand your strengths and areas for growth.
• Has witnessed your academic or professional development.
• Is familiar with your goals.
• Believe in your potential to achieve those goals.

Professional Letter of Recommendation: Guidelines for Top Universities

When universities consider applicants for graduate programs, they seek candidates who can thrive under mentorship and deliver strong results. They want individuals who are deeply committed and focused on their chosen field.

Letters of recommendation play a key role in identifying these ideal candidates. Below, you’ll find the requirements for a professional letter of recommendation from some of the most renowned institutions.

Crafting a strong professional letter of recommendation is crucial when applying to highly competitive universities like Oxford and Stanford, which often require three such letters. A well-written LOR can significantly enhance your application by providing a personalised perspective on your academic abilities, character, and potential. 

A compelling letter can help you stand out among talented applicants by highlighting your strengths and accomplishments. It will increase your chances of securing admission to your dream institution. Are you looking to get a solid professional letter of recommendation? Leap Scholar’s experts are here to help you craft the perfect LOR and guide you through every step of the application process. Book a consultation today and take the first step toward your academic success.

Frequently Asked Questions

Q. what is a professional letter of recommendation.

A. A professional letter of recommendation is written by someone who knows you well, such as a professor, supervisor, or mentor, and can vouch for your skills, character, and qualifications. Universities or employers often require this letter to provide an external, objective assessment of your abilities, work ethic, and potential.

Q. Why do I need a professional letter of recommendation for a graduate program?

A. A professional letter of recommendation is crucial for graduate program applications because it gives admissions committees a trusted, third-party perspective on your abilities and readiness for advanced study. While your academic transcripts and personal statements showcase your achievements and goals, a letter of recommendation offers a deeper insight into your work ethic, character, and interaction in professional or academic settings. 

Q. Who should I ask to write my professional letter of recommendation?

A. You should ask someone who knows you well and can provide a detailed, positive assessment of your qualifications. Ideal recommenders include professors who have taught you in courses related to your intended field of study, supervisors who have overseen your work on significant projects, or mentors who have guided you in your academic or professional development. 

Q. How many letters of recommendation do top universities typically require?

A. Top universities, such as Oxford, Stanford, and Princeton, typically require three letters of recommendation for their graduate program application process. These letters are expected to come from individuals who can provide distinct perspectives on your abilities and character. For example, one letter might focus on your academic achievements, another on your research skills, and a third on your professional experience.

Q. What should be included in a professional letter of recommendation?

A. A professional, solid letter of recommendation should include several key elements to support your application effectively. It should begin with an introduction establishing the recommender’s relationship with you and their qualifications to speak on your behalf. The letter’s body should summarise your key strengths, supported by specific examples of your achievements and contributions in academic or professional settings.

Q. How long should a professional letter of recommendation be?

A. A professional letter of recommendation is typically 1-2 pages long, consisting of 5-6 well-structured paragraphs. The length allows the recommender to thoroughly assess your qualifications without overwhelming the reader. Each paragraph should focus on your skills or character, such as your academic abilities, research experience, leadership qualities, or personal integrity. 

Q. What format should a professional letter of recommendation follow?

A. The letter should be formatted according to standard professional guidelines. This includes 1-inch margins, single-spaced lines, and left-aligned text. The font should be according to and experienced, such as Times n, with a size between 10 and 12 points. The letter should include a formal salutation, a clear introduction, a detailed body, and a strong closing statement. 

Q. Can I use the same letter of recommendation for multiple applications?

A. While it’s possible to use the same recommender for multiple applications, it’s generally best to have them tailor each letter to the specific program or job you’re applying to. Different programs may value different qualities or experiences, so a one-size-fits-all letter may not highlight the most relevant aspects of your background. 

Q. What is the difference between a professional letter of recommendation and a reference letter?

A. A professional letter of recommendation is typically more detailed and formal than a reference letter. It focuses on your qualifications for a specific program or job and is often written by someone who has closely supervised your academic or professional work. On the other hand, a reference letter might be more general and can come from a broader range of individuals, such as a colleague or a community leader. 

Q. How can I help my recommender write a strong letter of recommendation?

A. To help your recommender write a strong letter of recommendation, provide them with detailed information about your goals, achievements, and the specific requirements of the program or job you’re applying to. Share your resume, a statement draft, and other relevant documents highlighting your qualifications.

Q. How can a professional letter of recommendation improve my chances of admission?

A. A well-written letter of recommendation can significantly enhance your application by providing a credible, third-party endorsement of your abilities, character, and potential. This external validation can reinforce the claims you’ve made in your statement and other application materials, helping to build a more compelling case for your admission.

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Hi, I am Prachi, an experienced writer with extensive knowledge about the study abroad domain in particular countries such as the USA and Canada and other popular courses. My expertise in SEO allows me to create high-quality content that engages and informs students and helps them fulfil their International Dreams.

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• How to Write a Consent Letter: Format and Samples

Consent Letter Format - Guidelines and Samples for Writing a Formal Consent Letter

A consent letter is a formal letter or document used to grant permission or approval for specific actions or decisions. Whether you need to permit a child’s school activity, approve a business transaction, or allow someone to access personal information, writing a clear and precise consent letter is essential. On this page, we guide you through the process of writing a well-structured consent letter, including key components to include and common mistakes to avoid.

How to write a consent letter better, we provide consent letter format for different scenarios. These samples will illustrate how to articulate your consent effectively, ensuring that your letter meets all requirements. By exploring these examples, you'll gain a better understanding of how to create your consent letter with confidence and accuracy.

What is a Consent Letter?

A consent letter is a formal document where one party gives permission or authorisation for a specific action, event, or procedure. It is commonly used in various contexts, such as medical procedures, school trips, and legal agreements. The letter clearly outlines the consent, purpose, and any conditions attached.

How to Write a Consent Letter

Title the Letter : Start with a clear title, such as "Consent Letter" or "Permission Letter."

Include Your Contact Information : At the top of the letter, include your name, address, phone number, and email address.

Date the Letter : Write the date the letter is being written.

Add the Recipient’s Details : Include the name, title, and address of the person or organisation receiving the letter.

State the Purpose : Mention the letter's purpose and what you consent to. Be specific about the details.

Provide Details : Include any relevant details about the consent, such as dates, locations, and conditions.

Sign and Date : End with your signature and date. If applicable, include a place for a witness's signature.

Contact Information : Offer a way for the recipient to contact you if needed.

Consent Letter Format

Your Name Your Address City, State, ZIP Code Phone Number Email Address

Recipient's Name Recipient's Title Recipient's Organisation Recipient's Address City, State, ZIP Code

Dear (Recipient's Name),

Subject: Consent for (Purpose)

I am writing to give my consent for (specific purpose, event, or action). This consent is provided for (provide any details or conditions).

Event/Action: (Describe what you are consenting to)

Additional Conditions:

I understand that by providing this consent, I am allowing (describe what is being permitted) and acknowledge that (include any other relevant information).

Please do not hesitate to contact me at (Your Phone Number) or (Your Email Address) if you require further information or clarification.

Thank you for your attention to this matter.

(Your Signature) (Your Name)

Samples of Consent Letters

1. consent letter for a school trip.

(Your Name) (Your Address) (City, State, ZIP Code) (Phone Number) (Email Address)

(Teacher’s Name) (School Name) (School Address) (City, State, ZIP Code)

Dear (Teacher’s Name),

Subject: Consent for School Trip

I am writing to give my consent for my child, (Child’s Name), to participate in the upcoming school trip to (Destination) on (Date). I understand that the trip will involve (briefly describe activities, if known), and I agree to all the planned activities.

Trip Destination: (Destination)

Date: (Date)

Special Instructions: (Any special instructions or medical information)

Please ensure that all necessary precautions are taken for the safety and well-being of the students. Should you need any additional information, feel free to contact me at (Your Phone Number) or (Your Email Address).

Thank you for organising this educational opportunity.

2. Permission Consent Letter for Medical Procedure

(Doctor’s Name) (Medical Facility’s Name) (Facility’s Address) (City, State, ZIP Code)

Dear (Doctor’s Name),

Subject: Consent for Medical Procedure

I, (Your Full Name), hereby give my consent for (Patient’s Full Name) to undergo (specific medical procedure or treatment) on (Date). I have been informed about the nature of the procedure, including any potential risks and benefits.

Procedure/Treatment: (Procedure/Treatment)

Additional Information: (Any additional information or special considerations)

I understand that I have the right to withdraw consent at any time before the procedure begins. Please contact me at (Your Phone Number) or (Your Email Address) if you require any further information.

Thank you for your attention.

Key Elements of a Consent Letter

Title and purpose:.

Clearly state that the document is a consent letter and specify the purpose of the consent. This helps to immediately convey the intent of the letter.

Personal Information:

Sender’s Details : Include your full name, address, contact number, and email address to provide a point of contact in the consent letter for a school trip or any other letter.

Recipient’s Details : Include the name, title, and address of the person or organisation receiving the consent to ensure the letter is directed to the right party.

The date of writing is important as it establishes when the consent was given and can be relevant for record-keeping.

Statement of Consent:

Clearly state what you are consenting to such as a permission consent letter, including any specific actions, events, or procedures. Be explicit to avoid any misunderstandings.

Details and Conditions:

Provide any necessary details, such as dates, locations, and conditions. This might include medical conditions, special instructions, or specific terms under which the consent is granted.

Acknowledgment of Risks and Benefits:

In some cases, especially for medical procedures, you might need to acknowledge that you are aware of the potential risks and benefits associated with the action or procedure.

Revocation of Consent:

Mention if and how you can withdraw or alter your consent if needed. This is particularly important for consent related to ongoing or future actions.

The letter should be signed to validate the consent. In some cases, a witness’s signature might also be required, especially for legal or medical consent.

Contact Information:

Offer additional contact information in case the recipient needs to follow up or clarify any details.

A few More Examples of Consent Letters

1. consent letter for a research study.

(Researcher's Name) (Research Institution/Organisation) (Institution’s Address) (City, State, ZIP Code)

Dear (Researcher’s Name),

Subject: Consent for Participation in Research Study

I, (Your Full Name), hereby give my consent to participate in the research study titled "(Study Title)" conducted by (Researcher’s Name) at (Institution/Organisation). I understand that the study involves (a brief description of the study, including procedures and objectives).

Study Details:

Study Title : (Study Title)

Purpose of Study : (Brief description)

Procedures : (Outline what will be required of you)

Duration : (Estimated time commitment)

Risks and Benefits : (Summary of potential risks and benefits)

Confidentiality : (Information on how your data will be protected)

I have been allowed to ask questions and have received satisfactory answers. I understand that participation is voluntary, and I may withdraw at any time without penalty.

Please contact me at (Your Phone Number) or (Your Email Address) if further information is needed.

Thank you for considering my participation.

2. Consent Letter for Use of Image/Photograph

(Recipient's Name) (Organisation/Company Name) (Address) (City, State, ZIP Code)

Dear (Recipient’s Name),

Subject: Consent for Use of Image/Photograph

I, (Your Full Name), hereby give my consent to (Organisation/Company Name) to use my image/photograph taken on (Date) at (Location) for (specific purposes, e.g., marketing, website, promotional materials).

Purpose of Use : (Describe how the image/photograph will be used)

Duration of Use : (Specify the period during which the image may be used)

Scope : (Clarify if there are any restrictions or if it will be used globally)

I understand that I will not receive any compensation for the use of my image/photograph and that it may be used in various media formats.

Should you require further information, please contact me at (Your Phone Number) or (Your Email Address).

3. Consent Letter for Granting Power of Attorney

(Recipient's Name) (Recipient's Title) (Recipient's Address) (City, State, ZIP Code)

Subject: Consent to Grant Power of Attorney

I, (Your Full Name), residing at (Your Address), hereby grant power of attorney to (Attorney’s Full Name) of (Attorney’s Address) to act on my behalf in all matters related to (specific legal or financial matters).

Scope of Authority : (Outline the specific powers granted)

Duration : (Specify the period for which the power of attorney is valid, if applicable)

Limitations : (Include any limitations or restrictions, if any)

I understand that this power of attorney is being granted voluntarily and that I have the right to revoke it at any time by providing written notice.

Please contact me at (Your Phone Number) or (Your Email Address) if you need additional information or clarification.

4. Consent Letter for a Student Internship

(Internship Coordinator’s Name) (Company/Organisation Name) (Company’s Address) (City, State, ZIP Code)

Dear (Internship Coordinator’s Name),

Subject: Consent for Student Internship

I, (Your Full Name), the parent/guardian of (Student’s Full Name), give consent for (Student’s Full Name) to undertake an internship with (Company/Organisation Name) from (Start Date) to (End Date).

Internship Details:

Internship Role : (Describe the role or tasks)

Duration : (Start Date - End Date)

Hours of Work : (Specify working hours, if known)

I understand that (Student’s Full Name) will be expected to adhere to the company's policies and procedures and will receive valuable experience during this period.

Please feel free to contact me at (Your Phone Number) or (Your Email Address) for any further information or clarification.

Thank you for providing this opportunity.

Each consent letter should be tailored to the specific situation and include all necessary details to ensure clarity and prevent any misunderstandings.

Test Your Knowledge: Consent Letters

1. What is the primary purpose of a consent letter?

a) To request approval for a project b) To grant permission or authorisation for a specific action, event, or procedure c) To provide feedback on a service d) To apply for a loan

2. Which section in a consent letter outlines what action or event you are granting permission for?

a) Personal Information b) Statement of Consent c) Acknowledgment of Risks and Benefits d) Signature and Date

3. True or False: A consent letter should always include the contact information of both the sender and the recipient.

4. In a consent letter for medical procedures, what is typically included to ensure the recipient understands the risks and benefits?

a) Contact details of the medical facility b) A detailed description of the procedure and its potential risks and benefits c) A list of all medical staff involved d) Personal medical history

5. Which of the following is NOT a typical type of consent letter?

a) Parental Consent Letter for a School Trip b) Consent for Use of Image/Photograph c) Consent for Academic Transcript Release d) Consent for Job Interview

Test Your Knowledge: Correct Answers

1: b) To grant permission or authorisation for a specific action, event, or procedure

2: b) Statement of Consent

4 : b) A detailed description of the procedure and its potential risks and benefits

5: d) Consent for Job Interview

Takeaways from this Page

Purpose : A consent letter grants permission or authorisation for specific actions, events, or procedures, ensuring clarity and agreement.

Key Components : Include a clear title, sender and recipient information, date, a detailed statement of consent, relevant details or conditions, and a signature.

Types : Common types include medical consent letters, parental consent for school activities, legal consent letters (e.g., power of attorney), and consent for the use of images.

Specificity : Be precise and detailed about what is being consented to and any associated risks or conditions to avoid misunderstandings.

Withdrawal : Include information on how to withdraw consent if needed, typically requiring written notice. Some documents, like legal consent, may need notarisation.

FAQs on How to Write a Consent Letter: Format and Samples

1. What is a consent letter?

A consent letter is a formal document used to grant permission or authorisation for a specific action, event, or procedure. It ensures that all parties involved understand and agree to the terms.

2. What should be included in a consent letter?

A consent letter should include the title, sender and recipient’s details, date, statement of consent, relevant details or conditions, acknowledgment of risks (if applicable), and signature.

3. How do I format a consent letter?

Start with a clear title, followed by the sender's contact information, date, recipient’s contact information, a clear statement of consent, relevant details, and a signature. Include any additional instructions or conditions.

4. Can a consent letter be informal?

While some contexts might allow for less formality, a consent letter should generally be formal to ensure clarity and legal validity. Use a professional tone and format.

5. When is a consent letter needed?

A consent letter is needed when formal permission is required for actions such as medical procedures, school activities, legal matters, or the use of personal images.

6. How specific should a consent letter be?

It should be very specific, including details such as dates, locations, procedures, and any conditions. This helps avoid misunderstandings and ensures clear communication.

7. What is the difference between a consent letter and a permission slip?

A permission slip is usually more informal and often used for school-related activities. A consent letter is more formal and may be required for legal, medical, or significant activities.

8. How can I withdraw consent after submitting a consent letter?

You can withdraw consent by providing written notice to the recipient, specifying your intent to withdraw and any relevant details. Ensure you follow any procedures outlined in the original consent letter.

9. Is it necessary to include a section on risks and benefits in a consent letter?

It is necessary for consent letters related to medical procedures or research studies where understanding risks and benefits is crucial. For other types of consent, this section might not be required.

10. What should I do if I make a mistake in a consent letter?

If there is a mistake, correct it clearly and initial the correction or issue a new letter with the correct information. Ensure that all parties receive the updated version.

11. Can a consent letter be used for international purposes?

Yes, but be aware of any specific legal requirements or regulations in the other country. The letter should be clear and may need to comply with international standards or be translated if necessary.

12. What are some examples of consent letters?

Examples include:

Medical Consent Letter: Grants permission for a medical procedure.

Parental Consent Letter: Consent letter for a school trip.

Consent for Use of Image: Authorises the use of personal photographs or permission consent letter.

Legal Consent Letter: Grants power of attorney or other legal permissions.

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• Research paper

Writing a Research Paper Introduction | Step-by-Step Guide

Published on September 24, 2022 by Jack Caulfield . Revised on March 27, 2023.

The introduction to a research paper is where you set up your topic and approach for the reader. It has several key goals:

• Present your topic and get the reader interested
• Provide background or summarize existing research
• Position your own approach
• Detail your specific research problem and problem statement
• Give an overview of the paper’s structure

The introduction looks slightly different depending on whether your paper presents the results of original empirical research or constructs an argument by engaging with a variety of sources.

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Table of contents

Step 1: introduce your topic, step 2: describe the background, step 3: establish your research problem, step 4: specify your objective(s), step 5: map out your paper, research paper introduction examples, frequently asked questions about the research paper introduction.

The first job of the introduction is to tell the reader what your topic is and why it’s interesting or important. This is generally accomplished with a strong opening hook.

The hook is a striking opening sentence that clearly conveys the relevance of your topic. Think of an interesting fact or statistic, a strong statement, a question, or a brief anecdote that will get the reader wondering about your topic.

For example, the following could be an effective hook for an argumentative paper about the environmental impact of cattle farming:

A more empirical paper investigating the relationship of Instagram use with body image issues in adolescent girls might use the following hook:

Don’t feel that your hook necessarily has to be deeply impressive or creative. Clarity and relevance are still more important than catchiness. The key thing is to guide the reader into your topic and situate your ideas.

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This part of the introduction differs depending on what approach your paper is taking.

In a more argumentative paper, you’ll explore some general background here. In a more empirical paper, this is the place to review previous research and establish how yours fits in.

Argumentative paper: Background information

After you’ve caught your reader’s attention, specify a bit more, providing context and narrowing down your topic.

Provide only the most relevant background information. The introduction isn’t the place to get too in-depth; if more background is essential to your paper, it can appear in the body .

Empirical paper: Describing previous research

For a paper describing original research, you’ll instead provide an overview of the most relevant research that has already been conducted. This is a sort of miniature literature review —a sketch of the current state of research into your topic, boiled down to a few sentences.

This should be informed by genuine engagement with the literature. Your search can be less extensive than in a full literature review, but a clear sense of the relevant research is crucial to inform your own work.

Begin by establishing the kinds of research that have been done, and end with limitations or gaps in the research that you intend to respond to.

The next step is to clarify how your own research fits in and what problem it addresses.

Argumentative paper: Emphasize importance

In an argumentative research paper, you can simply state the problem you intend to discuss, and what is original or important about your argument.

Empirical paper: Relate to the literature

In an empirical research paper, try to lead into the problem on the basis of your discussion of the literature. Think in terms of these questions:

• What research gap is your work intended to fill?
• What limitations in previous work does it address?
• What contribution to knowledge does it make?

You can make the connection between your problem and the existing research using phrases like the following.

Now you’ll get into the specifics of what you intend to find out or express in your research paper.

The way you frame your research objectives varies. An argumentative paper presents a thesis statement, while an empirical paper generally poses a research question (sometimes with a hypothesis as to the answer).

Argumentative paper: Thesis statement

The thesis statement expresses the position that the rest of the paper will present evidence and arguments for. It can be presented in one or two sentences, and should state your position clearly and directly, without providing specific arguments for it at this point.

Empirical paper: Research question and hypothesis

The research question is the question you want to answer in an empirical research paper.

Present your research question clearly and directly, with a minimum of discussion at this point. The rest of the paper will be taken up with discussing and investigating this question; here you just need to express it.

A research question can be framed either directly or indirectly.

• This study set out to answer the following question: What effects does daily use of Instagram have on the prevalence of body image issues among adolescent girls?
• We investigated the effects of daily Instagram use on the prevalence of body image issues among adolescent girls.

If your research involved testing hypotheses , these should be stated along with your research question. They are usually presented in the past tense, since the hypothesis will already have been tested by the time you are writing up your paper.

For example, the following hypothesis might respond to the research question above:

Scribbr Citation Checker New

The AI-powered Citation Checker helps you avoid common mistakes such as:

• Missing commas and periods
• Incorrect usage of “et al.”
• Ampersands (&) in narrative citations
• Missing reference entries

The final part of the introduction is often dedicated to a brief overview of the rest of the paper.

In a paper structured using the standard scientific “introduction, methods, results, discussion” format, this isn’t always necessary. But if your paper is structured in a less predictable way, it’s important to describe the shape of it for the reader.

If included, the overview should be concise, direct, and written in the present tense.

• This paper will first discuss several examples of survey-based research into adolescent social media use, then will go on to …
• This paper first discusses several examples of survey-based research into adolescent social media use, then goes on to …

Full examples of research paper introductions are shown in the tabs below: one for an argumentative paper, the other for an empirical paper.

• Argumentative paper
• Empirical paper

Are cows responsible for climate change? A recent study (RIVM, 2019) shows that cattle farmers account for two thirds of agricultural nitrogen emissions in the Netherlands. These emissions result from nitrogen in manure, which can degrade into ammonia and enter the atmosphere. The study’s calculations show that agriculture is the main source of nitrogen pollution, accounting for 46% of the country’s total emissions. By comparison, road traffic and households are responsible for 6.1% each, the industrial sector for 1%. While efforts are being made to mitigate these emissions, policymakers are reluctant to reckon with the scale of the problem. The approach presented here is a radical one, but commensurate with the issue. This paper argues that the Dutch government must stimulate and subsidize livestock farmers, especially cattle farmers, to transition to sustainable vegetable farming. It first establishes the inadequacy of current mitigation measures, then discusses the various advantages of the results proposed, and finally addresses potential objections to the plan on economic grounds.

The rise of social media has been accompanied by a sharp increase in the prevalence of body image issues among women and girls. This correlation has received significant academic attention: Various empirical studies have been conducted into Facebook usage among adolescent girls (Tiggermann & Slater, 2013; Meier & Gray, 2014). These studies have consistently found that the visual and interactive aspects of the platform have the greatest influence on body image issues. Despite this, highly visual social media (HVSM) such as Instagram have yet to be robustly researched. This paper sets out to address this research gap. We investigated the effects of daily Instagram use on the prevalence of body image issues among adolescent girls. It was hypothesized that daily Instagram use would be associated with an increase in body image concerns and a decrease in self-esteem ratings.

The introduction of a research paper includes several key elements:

• A hook to catch the reader’s interest
• Relevant background on the topic
• Details of your research problem

and your problem statement

• A thesis statement or research question
• Sometimes an overview of the paper

Don’t feel that you have to write the introduction first. The introduction is often one of the last parts of the research paper you’ll write, along with the conclusion.

This is because it can be easier to introduce your paper once you’ve already written the body ; you may not have the clearest idea of your arguments until you’ve written them, and things can change during the writing process .

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.

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31 Great Content Writing Examples, Tips, and Tools

• by Ann Gynn
• | Published: August 21, 2024
• | Content Creation

Great content writing must be powerful and effective to captivate your audience.

But accomplishing that with your content writing isn’t an easy task. Whether you craft words for B2B or B2C audiences, the challenges can be many.

To help, I’ve compiled web writing examples, tips, tools, and resources. The goal is to give you some insights and new tools to help address or minimize the creation stumbling blocks web and content writers face.

Let’s get to it.

1. Go for the surprise

When you write something that’s unexpected, your audience will likely stop scrolling and take a moment to learn more. In the worst cases, this approach to content writing falls under the nefarious clickbait category. But in the best cases, it can delight and engage the viewer.

Nike is always a go-to source for the best content examples. The summer of 2024 didn’t disappoint with its Winning Isn’t for Everyone campaign.

With a debut in time for the global games, Nike featured the world’s greatest athletes (well, all the great Nike-sponsored athletes) talking about they are motivated by victory and that there’s nothing wrong with wanting to win. Writing those four words — winning isn’t for everyone — fosters a strong reaction. After all, there are far more people who don’t win than do. But audiences are also likely to watch more of the videos to learn what Nike is really talking about.

As you watch the video, note the repetition of the same question (“Am I a bad person?”) followed by short, staccato-paced statements. This approach creates a lyrical story. And it paid off, earning over 2.2 million views in two weeks.

2. Don’t forget text has a starring role in video

Words appear in blog posts or descriptions of product features and benefits. But writers can also shine in  video scripts, along with set designers, actors, and filmmakers. Writers can take any topic and help make it captivating.

J.P. Morgan used animation and strong scripts to explain finance-related concepts in its Unpacked series, a finalist in the Content Marketing Awards for best video. This 4.5-minute episode covers how private companies go public:

3. Tap into trends with simple writing prompts

I’m always a fan of Dove’s #KeepBeautyReal campaigns. Most recently, it created an example of powerful writing in this simple question, “ What kind of beauty do we want AI to learn?”

Capitalizing on the AI trend and interest, Dove illustrates the difference between AI-created images for prompts about “beautiful women” and “beautiful women according to Dove’s Real Beauty ads.” In the first three months of its debut, the video with few words has earned over 100K views on Dove’s YouTube channel and garnered mainstream and industry media attention.

4. Let your audience create great writing and video examples

Creativity can emerge in many ways. Sometimes, it’s a simple starting point that reflects the times, as Dove did in its content example.

It also may lead a brand to contribute to its own pop culture trend as The Stanley did with its Quencher Cup social media campaign in 2024 . Its influencer campaign prompted these fun user-generated examples of web writing and illustration in the form of memes and TikTok videos promoting the brand’s popular drinking vessel.

Hilarious Scales created this sample that’s been seen by over 10 million viewers:

@hilarious_scaless How yall be lookin with them Stanley Cups 🤣 #fypシ #fyp #stanleycup #stanleytumbler ♬ original sound – Hilarious_scales

Fans of hockey (that sport with the other Stanley Cup) also got into the action as Instagram account Daily Facebook shared this example:

View this post on Instagram A post shared by DailyFaceoff (@dailyfaceoff)

5. Nail down your headlines

I’ve said it often: Headlines are the powerhouse of your content writing. After all, if the headline isn’t a success, the content behind it will never be read.

A 2024 study published in Science Advance conducted over 30,000 field experiments with The Washington Post and Upworthy headlines. It found that readers prefer simpler headlines (more common words and more readable writing) over complex ones. They also paid more attention to and more deeply processed the simpler headlines.

The e-book headline in this example from OptinMonster is straightforward: 50 Smart Ways to Segment Your Email List. It uses a numeral (50), a helpful adjective (smart), and a second-person pronoun (your) to speak directly to the audience, all of which elevates the article’s value in the reader’s mind.

Image source

6. Analyze the potential impact of your content headlines

Size up headlines with the Advanced Marketing Institute’s Headline Analyzer , which reveals an emotional marketing value score.

This headline example — 14 Ways Marketing Automation Helps B2B Companies Succeed — earns an emotional marketing value (EMV) of 37.5%. Most professional copywriters’ headlines typically have a 30% to 40% EMV score.

The same headline in a similar tool, CoSchedule Blog Post Headline Analyzer , earns a score of 77 out of 100. This analysis looks at word balance, headline type, sentiment, reading grade level, clarity, and skimmability. It also identifies areas for improvement, such as the use of uncommon, emotional, and power words.

7. Adjust title formats with this content writing tool

Speed your formatting tasks with TitleCase . The tool converts your title into various circumstances — all caps, hyphen, etc., so you don’t have to rekey or reformat.

8. Write headlines with words that resonate

BuzzSumo research consistently identifies “how-to” or guidance-focused headlines that resonate far better with audiences than any other type.

It makes sense. Audiences are seeking information that will help them in their lives, and they have a lot of content from which to choose. By writing phrases like “how to” in a headline, you tell them clearly what they’re going to get.

Get more tips from CMI’s article How To Create Headlines That Are Good for Readers and Business .

9. Focus on clarity for web content

Explaining your product or service can get cumbersome, but it shouldn’t if you want the audience to quickly understand how your company can help solve their pain points.

In this example, Zendesk succinctly highlights three results gained by the enterprise clients of its customer service platform:

• Drive better conversations
• Maximize agent efficiency
• Adapt faster to change

The three- and four-word headlines are followed by short explanations (two sentences) and a link to the product’s relevant features for that category.

10. Write to win over readers

How does your content inspire readers or get them to care?

Some suggestions include:

• Focus on actionable content they could use right away.
• Establish instant credibility and expertise so they understand why you’re the go-to resource.
• Add value they wouldn’t see or find elsewhere.

This ad for the Content Marketing Institute newsletter works well as a sample of website content writing. It illustrates how to motivate the audience to see that the content is relevant for them. Its headline “Looking for Fresh Content Inspiration?” speaks directly to the reader. Its follow-up sentence explains in detail what the reader will get — expert advice, standout examples, and creative ideas.

11. Choose words that motivate actions

Sometimes, it’s a simple word or phrase that prompts someone to take the next step. Buffer offers a list of more than 150 words . These 19 words and phrases are examples of how to gain the audience’s trust:

• Bestselling
• Endorsed by
• Money-back guarantee
• No obligation
• No questions asked
• Recommended
• Transparent
• Try for free

In this web page example, OptinMonster opts for one of those words in its headline — How To Create a Fail-Proof Digital Marketing Plan in 5 Steps .

12. Keep it brief but convey a lot

Given your audience reads on screens, your web writing usually appears in a small space. Yet, it still must reflect a strong message.

For example, this American Express Business web copy uses five words to indicate that it gets the reader’s problem — “Don’t stress over seasonal surges.” Then, it uses another five words to indicate that it has a solution — “Help you keep your business thriving.” On the right, it shows the product name that will do all that (American Express business line of credit.)

13. Create compelling content with better words

Choosing a single word to convey the perfect sentiment makes the most of your available content space. To help, Jon Morrow of Smart Blogger offers a collection of words that can make a difference in your writing: 801+ Power Words That Make You Sound Smart . Here are 15 of them:

• Frightening

In this headline — Firefox Hacks for Everyone: From Cozy Gamers to Minimalists and Beyond — the Mozilla blog opted for one of the power words, “hack.”

 I’ll issue a caveat on this option: Power words can quickly become overused. “Hack” is coming close to saturation.

14. Length isn’t everything

I like to know content length rules and preferences. They give me guideposts for my web writing.

Google makes 30 characters available in its ad headlines, and it’s hard to go shorter than that. This simple sample — Best Enterprise CRM Platform — is 28 characters.

On social media, though, the character parameters are greater, and you could improve engagement by falling short of the upper limits.

Instagram is a perfect example of where writing content short of the 2,200-character maximum caption is a better decision. In fact, experts say the ideal length is 125 characters, which takes up the space visible before the viewer must click to read more.

Still, sometimes writing fewer than 125 characters can work well and draw attention in a crowded feed, as this sample from Grammarly shows. Its caption — “Learn actionable strategies for leveraging Gen AI to elevate your team’s productivity.” — totals just 88 characters.

Of course, exceptions exist. If your content’s primary goal is search engine optimization, longer content is almost always best. As a website ages, it may be able to get by with shorter pieces because it’s already established authority and has more pages, inbound links , etc. However, extended content often helps generate high rankings for targeted keyword phrases and similar words.

15. Choose short words for your web writing

You don’t need to use a lot of words to get your point across. Short ones can work in your favor. Consider these common examples of better choices:

• “Show,” not “indicate”
• “Get rid of,” not “eliminate”
• “Use,” not “utilize”
• “To,” not “in order to”
• “Help,” not “facilitate”
• “Get,” not “obtain”

16. Use a tool to keep track of word counts

Meet your word count goals and improve your word choice with the WordCounter tool. It also helps identify keywords and their appropriate frequency of use.

17. Recognize common writing mistakes

Grammar Girl , created by Mignon Fogarty, founder of Quick and Dirty Tips, outlines some common mistakes, such as this example on the use of that vs. which in writing.

“The simple rule is to use ‘that’ with a restrictive element and ‘which’ with a non-restrictive element … The cupcakes that have sprinkles are still in the fridge. The words “that have sprinkles” restrict the kind of cupcake we’re talking about. Without those words, the meaning of the sentence would change. Without them, we’d be saying that all the cupcakes are still in the fridge, not just the ones with sprinkles.”

18. Use parallel construction

Parallel construction organizes the text and relieves your readers of expending mental energy to piece together the thoughts.

• For example, this mish-mash list is not parallel because the sentence structures vary:
• It could be time to look over your business software contract.
• Consider the best products.
• If you want the product to benefit your company, include others’ points of view.

The list is parallel because every sentence starts the same way – with a verb .

• Review your business software contract.
• Shop for the best products based on features, costs, and support options.
• Ask key members of your team for their perspectives, including productivity barriers.

19. Know when to break the infinitive rule

Avoid splitting infinitives. However, sometimes you might need to bypass grammatically correct in favor of unawkward content.

Pro Writing Aid explains that split infinitives are nothing new — their use dates back to the 1300s. However, there is a time and place for them, as shown in this example from Northern Illinois University’s Effective Writing Practices Tutorial :

• Split infinitive but easily understood: It’s hard to completely follow his reasoning.
• No split infinitive, but awkwardly written: It’s hard to follow completely his reasoning.

20. Be conscious of pronouns

A conversational approach typically works best when you’re creating web content. Writing in the first or second person can accomplish this.

Embracing inclusivity also fosters a conversational atmosphere.

When you’re using pronouns, make sure it’s clear to what the pronoun refers. Given some people use they/them pronouns, ensuring pronoun clarity is especially important.

In those cases where the reader may be confused, explain the person’s use of the plural non-gendered pronoun in the text, for example, “Alex Alumino, who uses they/them pronouns …” Even better, just repeat their name in the sentence so there’s no need to explain and no misunderstanding.

21. Don’t overuse words

Redundancy bores. To figure out if you’re committing this sin, paste your text into the Word It Out tool. The word cloud reveals those used most often in your text.

We input a recent CMI article about user stories to create a word cloud for that content sample. It is no surprise that “user” shows up front and center, but it’s also an indicator for us to review the article to see if “user” is overused. “Katie” also shows up prominently in the word cloud as it’s the first name of the source for the article, and CMI uses first, instead of last names, on second and subsequent references. A review of the article could reveal it unnecessarily references the source too many times.

Similarly, WordCounter detects whether you’re using the same words too often. Use Thesaurus.com to find alternatives.

22. Try this content writing tool to replace jargon-like words

You need to speak your audience’s language, but that doesn’t mean you need to adopt the industry’s jargon. De-Jargonizer is designed to help analyze the jargon in scholarly articles, but the tool works just as well with your content writing.

In this example from a CMI article about building a social media plan , De-Jargonizer identifies four “rare” words — ebbs, inhospitable, clarifies, and actionable.

You can upload a file or paste your text to discover those rare words, aka potential jargon, in your content writing. Then, you can find more reader-friendly replacements.

23. Check your readability score

Even if readers can understand the jargon and complex sentences, they still don’t want to work hard to understand your content. To help understand if your writing is on the easier side, use a tool like Web FX’s Readability Test . It scores your content’s average reading ease and targeted readership age.

In this example, it evaluates the Fedex.com website and concludes it has a reading ease of 27.8 out of 100 and is targeted at 14- and 15-year-olds.

You can scroll down to see other readability scores, including Flesch Kincaid reading ease, Flesch Kincaid grade level, Gunning Fog, Smog Index, Coleman Liau, and Automated Readability Index.

The bottom of the evaluation includes the statistics about the evaluated text, including:

• Total sentences
• Total words
• Complex words
• Percent of complex words
• Average words per sentence
• Average syllables per word

Adjust your writing to meet the preferred readership level of your audience.

24. Evaluate sentence structure with the Hemingway App

Want more help to write content that’s easy to read? Consider tools like the Hemingway app, which provides immediate and detailed feedback on content structure, including sentence formatting. With the website version, you can replace the default text with your own.

The Hemingway app identifies potentially unnecessary adverbs, warns about passive voice, and triggers alerts to dull, complicated words.

In this web writing example from its home page, Hemingway App highlights one of the 13 sentences as very hard to read, one as hard to read, two weakener phrases, and one word with a simpler alternative.

25. Get web writing right with good grammar

Proper grammar is a necessity; you want to get everything correct to satisfy readers (and bosses). Try Grammarly .

Improve your writing with this cloud-based, AI editor. Grammarly automates grammar, spelling, and punctuation checks, often giving better, cleaner content options. The tool also alerts writers to passive voice, suggests opportunities to be concise, and assesses overall tone.

You also can save time and energy with ProWritingAid . It eliminates the need to reread to polish your content. This AI editing software offers more than grammar checks. It checks for vague wording, sentence length variation, and overuse of adverbs and passive voice. The tool also identifies complicated or run-on sentences. (“Content Writing Examples, Tips, and Resources”)

26. Read your web content in scanning mode

Here’s some sad news for content writers: Readers won’t consume every word in your content. They skip and scan a lot to see if the content is a good fit for them, and then they hope they can glean the relevant information without having to consume all the content.

As you write, think about how the text will look visually. Make it easy for readers to scan your content by including:

• Short paragraphs
• Bulleted lists
• Bolded text
• Words in color

27. Read aloud

If your content doesn’t flow as you speak it, it may not work for the reader . Pay attention to when you take too many pauses or pause in places where no comma exists. Adjust your text — add a comma or break the sentence into two.

Microsoft Word offers a read-aloud feature through its immersive reader tools, while Google Docs can use a Chrome extension to give a voice to the content .

28. Use plagiarism checkers

In recent years, advancements in artificial intelligence have prompted growth in automated plagiarism checkers. Microsoft Word embeds the feature option in its software as does Grammarly. You also can use tools dedicated to ensuring that the content writing isn’t a copycat (or being copycatted), including:

• Unicheck – Verify the originality of work with plagiarism detection. You can spot outright copying and minor text modifications in unscrupulous submissions.
• Copyscape – Protect your content and your reputation. Copyscape uncovers plagiarism in purchased content and detects plagiarism by others of your original work.

Of course, no plagiarism checker is 100% accurate, so before you accuse a content writer of plagiarism, triple-check the results (and add a human touch whenever appropriate).

29. Use a topic tool for writing inspiration

HubSpot’s Ideas Generator works well to get your creative content writing juices flowing. Just fill in the fields with three nouns to get some ideas.

For example, if you input the words car, truck, and SUV, HubSpot delivers these ideas along with the targeted keywords for the topic:

• Keyword: Top truck accessories
• Keyword: Comparing SUV models
• Keyword: Truck bed organization ideas

HubSpot’s topic generator also allows users to pick a title and have an outline created for that article.

You also could perform a similar exercise by writing the prompts in other generative AI tools, such as ChatGPT and Gemini .

NOTE: Always review the titles and accompanying data to ensure accuracy. In the HubSpot sample, the generator included a headline — Discover the Best SUVs for Families in 2021. Yet, it’s 2024.

30. Know SEO responsibilities in web writing

Sometimes writers create content with multiple purposes. They have the burden of blending SEO into the content . I frame it as a burden because it’s one more variable to deal with. If you have a knack for SEO and goals you can measure, it’s not a burden.

Unfortunately, you sometimes don’t know what realistic keywords to pursue. Aim too low and you use rarely searched keywords. Aspire for something too competitive, and the content won’t rank.

How are you evaluating keywords? Learn how to find your sweet spot with keyword selection (and how to appear on the first page of Google). Identify potential keywords by using tools like:

• Moz Keyword Explorer
• Google’s Keyword Planner
• Keyword Tool
• AnswerThePublic
• Neil Patel’s Ubersuggest

31. Monitor relevant topics to get ideas for your content

With Feedly , you can stay informed about what matters most and avoid information overload. This AI assistant learns your preferences, then culls and curates content from the internet that you want and need.

Share your favorite writing tricks

What content creation and copywriting productivity tools do you favor? What do you do each day to make your writing tasks just a little easier? Please tag CMI on social media using #CMWorld.

All tools mentioned in this article were suggested by the author. If you’d like to suggest a tool, share the article on social media with a comment.

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Cover image by Joseph Kalinowski/Content Marketing Institute