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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.

Quantitative and Qualitative Research: An Overview of Approaches

• First Online: 03 January 2022

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In Chap. 1 , the nature and scope of research were outlined and included an overview of quantitative and qualitative research and a brief description of research designs. In this chapter, both quantitative and qualitative research will be described in a little more detail with respect to essential features and characteristics. Furthermore, the research designs used in each of these approaches will be reviewed. Finally, this chapter will conclude with examples of published quantitative and qualitative research in medical imaging and radiation therapy.

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Seeram, E. (2021). Quantitative and Qualitative Research: An Overview of Approaches. In: Seeram, E., Davidson, R., England, A., McEntee, M.F. (eds) Research for Medical Imaging and Radiation Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-79956-4_2

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• Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

Table of contents

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

• Surveys :  List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
• Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
• Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

• Interviews : Asking open-ended questions verbally to respondents.
• Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
• Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
• Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

• Use quantitative research if you want to confirm or test something (a theory or hypothesis )
• Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

• Average scores ( means )
• The number of times a particular answer was given
• The correlation or causation between two or more variables
• The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

• Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
• Thematic analysis : Closely examining the data to identify the main themes and patterns
• Discourse analysis : Studying how communication works in social contexts

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Qualitative VS Quantitative Definition – Research Methods and Data

When undertaking any type of research study, the data collected will fall into one of two categories: qualitative or quantitative. But what exactly is the difference between these two data types and research methodologies?

Put simply, quantitative data deals with numbers, objective facts and measurable statistics. For example, quantitative data provides specifics on values like website traffic metrics, sales figures, survey response rates, operational costs, etc.

Qualitative data , on the other hand, reveals deeper insights into people‘s subjective perspectives, experiences, beliefs and behaviors. Instead of numbers, qualitative findings are expressed through detailed observations, interviews, focus groups and more.

Now let‘s explore both types of research to understand how and when to apply these methodologies.

Qualitative Research: An In-Depth Perspective

The purpose of qualitative research is to comprehend human behaviors, opinions, motivations and tendencies through an in-depth exploratory approach. Qualitative studies generally seek to answer "why" and "how" questions to uncover deeper meaning and patterns.

Key Features of Qualitative Research

• Exploratory and open-ended data collection
• Subjective, experiential and perception-based findings
• Textual, audio and visual data representation
• Smaller purposeful sample sizes with participants studied in-depth
• Findings provide understanding and context around human behaviors

Some examples of popular qualitative methods include:

• In-depth interviews – Open discussions exploring perspectives
• Focus groups – Facilitated group discussions
• Ethnographic research – Observing behaviors in natural environments
• Content analysis – Studying documents, images, videos, etc.
• Open-ended surveys or questionnaires – Subjective questions

The benefit of these techniques is collecting elaborate and descriptive qualitative data based on personal experiences rather than just objective facts and figures. This reveals not just what research participants are doing but more importantly, why they think, feel and act in certain ways.

For example, an open-ended survey may find that 52% of respondents felt "happy" about using a particular smartphone brand. But in-depth interviews would help uncover exactly why they feel this way by collecting descriptive details on their user experience.

In essence, qualitative techniques like interviews and ethnographic studies add crucial context . This allows us to delve deeper into research problems to gain meaningful insights.

Quantitative Research: A Data-Driven Approach

Unlike qualitative methods, quantitative research relies primarily on the collection and analysis of objective, measurable numerical data. This structured empirical evidence is then manipulated using statistical, graphical and mathematical techniques to derive patterns, trends and conclusions.

Key Aspects of Quantitative Research

• Numerical, measurable and quantifiable data
• Objective facts and empirical evidence
• Statistical, mathematical or computational analysis
• Larger randomized sample sizes to generalize findings
• Research aims to prove, disprove or lend support to existing theories

Some examples of quantitative methods include:

• Closed-ended surveys with numeric rating scales
• Multiple choice/dichotomous questionnaires
• Counting behaviors, events or attributes as frequencies
• Scientific experiments generating stats and figures
• Economic and marketing modeling based on historical data

For instance, an online survey may find that 74% of respondents rate a particular laptop 4 or higher on a 5-point scale for quality. Or an experiment might determine that a revised checkout process increases e-commerce conversion rates by 14.5%.

The benefit of quantitative data is that it generates hard numbers and statistics that allow objective measurement and comparison between groups or changes over time. But the limitation is it lacks detailed insights into the subjective reasons and context behind the data.

Qualitative vs. Quantitative: A Comparison

Is Qualitative or Quantitative Research Better?

Qualitative and quantitative methodologies have differing strengths and limitations. Expert researchers argue both approaches play an invaluable role when combined effectively .

Qualitative research allows rich exploration of perceptions, motivations and ideas through open-ended inquiry. This generates impactful insights but typically with smaller sample sizes focused on depth over breadth.

Quantitative statistically analyzes empirical evidence to uncover patterns and test hypotheses. This lends generalizable support to relationships between variables but risks losing contextual qualitative detail.

In short, qualitative informs the human perspectives while quantitative informs the overarching trends. Together this approaches a problem from both a granular and big-picture level for robust conclusions.

Integrating Mixed Research Methods

Mixing qualitative and quantitative techniques leverages the strengths while minimizing the weaknesses of both approaches. This integration can happen sequentially in phases or concurrently in parallel strands:

Sequential Mixed Methods

• Initial exploratory qualitative data collection via interviews, ethnography etc.
• Develop hypotheses and theories based on qualitative findings
• Follow up with quantitative research to test hypotheses
• Interpret how quantitative results explain qualitative discoveries

Concurrent Mixed Methods

• Simultaneously collect both qualitative and quantitative data
• Merge findings to provide a comprehensive analysis
• Compare results between sources to cross-validate conclusions

This intermixing provides corroboration between subjective qualitative themes and hard quantitative figures to produce actionable insights.

Let‘s look at two examples of effective mixed methods research approaches.

Applied Examples of Mixed Methods

Hospital patient experience analysis.

A hospital administrator seeks to improve patient satisfaction rates.

Quantitative Data

• Statistical survey ratings for aspects like room cleanliness, wait times, staff courtesy etc.
• Rankings benchmarked over time and against other hospitals

Qualitative Data

• Patient interviews detailing frustrations, likes/dislikes and emotional journey
• Expert focus groups discussing challenges and brainstorming solutions

Combined Analysis

Statistical survey analysis coupled with patient interview narratives provides a robust perspective into precisely which issues most critically impact patient experience and what solutions may have the greatest impact.

Product Development Research

A technology company designs a new smartphone app prototype.

• App metric tracking showing feature usage frequencies, conversions, churn rates
• In-app surveys measuring ease-of-use ratings on numeric scales
• Moderated focus groups discussing reactions to prototype
• Diary studies capturing user challenges and delights

Metrics prove what features customers interact with most while qualitative findings explain why they choose to use or abandon certain app functions. This drives effective product refinement.

As demonstrated, thoughtfully blending quantitative and qualitative techniques can provide powerful multifaceted insights.

Tying It All Together: A Nuanced Perspective

Qualitative and quantitative research encompass differing but complementary methodological paradigms for understanding our world through data.

Qualitative research allows inquiry into the depths of human complexities – perceptions, stories, symbols and meanings. Meanwhile, quantitative methods enable us to zoom out and systematically analyze empirical patterns.

Leveraging both modes of discovery provides a nuanced perspective for unlocking insights. As analyst John Tukey noted, "The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data."

Rather than blindly following statistics alone, factoring in qualitative details allows us to carefully interpret the context and meaning behind the numbers.

In closing, elegantly integrating quantitative precision with qualitative awareness offers a multilayered lens for conducting research and driving data-savvy decisions.

Dr. Alex Mitchell is a dedicated coding instructor with a deep passion for teaching and a wealth of experience in computer science education. As a university professor, Dr. Mitchell has played a pivotal role in shaping the coding skills of countless students, helping them navigate the intricate world of programming languages and software development.

Beyond the classroom, Dr. Mitchell is an active contributor to the freeCodeCamp community, where he regularly shares his expertise through tutorials, code examples, and practical insights. His teaching repertoire includes a wide range of languages and frameworks, such as Python, JavaScript, Next.js, and React, which he presents in an accessible and engaging manner.

Dr. Mitchell’s approach to teaching blends academic rigor with real-world applications, ensuring that his students not only understand the theory but also how to apply it effectively. His commitment to education and his ability to simplify complex topics have made him a respected figure in both the university and online learning communities.

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Qualitative vs. Quantitative Research | Differences, Examples & Methods

When it comes to collecting, analyzing, and interpreting research findings, two primary approaches stand out - qualitative and quantitative methods. While both are essential for gaining a deeper understanding of various topics, they differ significantly in their approach, methodology, data collection techniques, analysis procedures, and the insights they provide.

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Quantitative Research: Numbers & Statistics

Quantitative research focuses on numerical values to test hypotheses or confirm theories through statistical analyses. This type involves collecting large datasets using methods such as surveys with closed-ended questions, experiments where variables are controlled and manipulated, observations in natural environments without control over variables, literature reviews of published works by other authors.

Quantitative data collection techniques include:

• Surveys: Distributed to a sample population via online platforms or face-to-face interactions.
• Experiments: Manipulating independent variables while controlling for confounding factors.
• Observations: Recording events in natural settings without intervention.

Common quantitative biases and limitations are information bias, omitted variable bias, sampling bias, selection bias.

Qualitative Research: Words & Meanings

Qualitative research focuses on the realm of words to understand concepts, thoughts, or experiences through open-ended questions during interviews, observations described verbally, literature reviews exploring theoretical frameworks.

Key qualitative data collection methods include:

• Interviews with in-depth questioning and follow-up clarification
• Observations where events are documented using descriptive language
• Literature Reviews examining existing theories & conceptualizations

Qualitative research is susceptible to biases such as the Hawthorne effect (observer influence), observer bias, recall bias, social desirability bias.

The Differences Between Quantitative vs. Qualitative Research Methods

Quantitative and qualitative approaches differ in their data collection methods, analysis procedures, and insights gained.

Data Collection Techniques

Both quantitative & qualitative research employ various techniques for collecting information; however some are more commonly associated with one type over the other

Commonly used both: Surveys (can be open-ended or closed), Observational studies (data can represent numbers e.g., rating scales) Case Studies.

Quantitative data collection methods tend to focus on numerical representations, whereas qualitative approaches emphasize descriptive language.

When Choosing Between Qualitative vs. Quantitative Research Methods

A general guideline for selecting between these two is:

Use quantitative research if you aim to confirm or test a hypothesis/theory Use qualitative research when seeking in-depth understanding of concepts/thoughts/experiences

Most topics allow the use of either, mixed-method approaches combining both are also viable options depending on your question(s), deductive vs. inductive approach and practical considerations such as time & resources.

Research Question

Example: How satisfied are students with their studies?

Quantitative Approach:

Survey 300 university students asking questions like "on a scale from 1-5, how do you rate professors?" Statistical analysis can reveal average ratings (e.g., 4.2).

Qualitative approach:

Conduct in-depth interviews using open-ended queries such as: “How satisfied are you with your studies?” Transcribe & analyze responses to identify common themes.

Mixed Methods Approach:

Combine both approaches by first conducting qualitative research through interviews, then quantifying the findings via a survey.

Analyzing Qualitative and Quantitative Data

Data analysis is crucial for extracting meaningful insights from collected data. The approach differs significantly between quantitative (numbers) and qualitative methods (words).

Quantitative Analysis: Numbers & Statistics

Use statistical software like Excel or SPSS to discover patterns, correlations/causations in numerical datasets.

Common analyses include:

• Average scores/means
• Frequency counts of specific answers
• Correlation/coefficient analysis for relationships among variables.
• Data Analysis for Decision Making - Quantitative Technique

Qualitative Data Analysis:

Analyze text-based data through various techniques such as content tracking (word frequency), thematic identification & discourse examination.

Some common qualitative approaches are: 

• Qualitative Content Analysis - examining word occurrences, positions and meanings.
• Thematic Analysis – closely analyzing the dataset to identify main themes/patterns
• Discourse analysis- studying communication dynamics in social contexts.
• Qualitative research within management

Ultimately understanding when to use each method depends on your research question(s), whether you're taking an inductive or deductive approach & practical considerations such as time, resources and access. By combining both qualitative and quantitative methods (mixed-method approaches) researchers can gain a more comprehensive view of their subject matter.

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Journal Article Reporting Standards (JARS)

APA Style Journal Article Reporting Standards offer guidance on what information should be included in all manuscript sections for quantitative, qualitative, and mixed methods research and include how to best discuss race, ethnicity, and culture.

Introducing Journal Article Reporting Standards for Race, Ethnicity, and Culture (JARS–REC)

JARS–REC were created to develop best practices related to the manner in which race, ethnicity, and culture are discussed within scientific manuscripts in psychological science.

Quantitative research

Use JARS–Quant when you collect your study data in numerical form or report them through statistical analyses.

Qualitative research

Use JARS–Qual when you collect your study data in the form of natural language and expression.

Mixed methods research

Use JARS–Mixed when your study combines both quantitative and qualitative methods.

Race, ethnicity, culture

Use JARS–REC for all studies for guidance on how to discuss race, ethnicity, and culture.

What are APA Style JARS?

APA Style Journal Article Reporting Standards (APA Style Jars ) are a set of standards designed for journal authors, reviewers, and editors to enhance scientific rigor in peer-reviewed journal articles. Educators and students can use APA Style JARS as teaching and learning tools for conducting high quality research and determining what information to report in scholarly papers.

The standards include information on what should be included in all manuscript sections for:

• Quantitative research ( Jars –Quant)
• Qualitative research ( Jars –Qual)
• Mixed methods research ( Jars –Mixed)

Additionally, the APA Style Journal Article Reporting Standards for Race, Ethnicity, and Culture ( Jars – Rec ) provide guidance on how to discuss race, ethnicity, and culture in scientific manuscripts. Jars – Rec should be applied to all research, whether it is quantitative, qualitative, or mixed methods.

• Race, Ethnicity, and Culture ( Jars – Rec )

Using these standards will make your research clearer and more accurate as well as more transparent for readers. For quantitative research, using the standards will increase the reproducibility of science. For qualitative research, using the standards will increase the methodological integrity of research.

Jars –Quant should be used in research where findings are reported numerically (quantitative research). Jars –Qual should be used in research where findings are reported using nonnumerical descriptive data (qualitative research). Jars –Mixed should be applied to research that includes both quantitative and qualitative research (mixed methods research). JARS–REC should be applied to all research, whether it is quantitative, qualitative, or mixed methods.

For more information on APA Style JARS:

• Read Editorial: Journal Article Reporting Standards
• View an infographic (PDF, 453KB) to learn about the benefits of JARS and how they are relevant to you
• Listen to a podcast with Drs. Harris Cooper and David Frost discussing JARS and implications for research in psychology

Many aspects of research methodology warrant a close look, and journal editors can promote better methods if we encourage authors to take responsibility to report their work in clear, understandable ways. —Nelson Cowan, Editor, Journal of Experimental Psychology: General

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Jars resources

• History of APA’s journal article reporting standards
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• JARS-Quant Decision Flowchart (PDF, 98KB)
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Jars articles

• Jars –Quant article
• Jars –Qual / Mixed article
• Jars – rec executive summary

Questions / feedback

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From the APA Style blog

Introducing APA Style Journal Article Reporting Standards for Race, Ethnicity, and Culture

These standards are for all authors, reviewers, and editors seeking to improve manuscript quality by encouraging more racially and ethnically conscious and culturally responsive journal reporting standards for empirical studies in psychological science.

APA Style JARS for high school students

In this post, we provide an overview of APA Style JARS and resources that can be shared with high school students who want to learn more about effective communication in scholarly research.

Happy 2022, APA Stylers!

This blog post is dedicated to our awesome APA Style users. You can use the many resources on our website to help you master APA Style and improve your scholarly writing.

APA Style JARS on the EQUATOR Network

The APA Style Journal Article Reporting Standards (APA Style JARS) have been added to the EQUATOR Network. The network aims to promote accuracy and quality in reporting of research.

APA Style JARS: Resources for instructors and students

APA Style Journal Article Reporting Standards (APA Style JARS) are a set of guidelines for papers reporting quantitative, qualitative, and mixed methods research that can be used by instructors, students, and all others reading and writing research papers.

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Speaker 1: Hello, and welcome back to this Global Health YouTube channel. My name's Greg Martin. We're going to do a few videos that look at study design and research methods. Now we're going to look at epidemiological research, we're going to look at the social sciences like anthropology, and essentially we're going to try and unpack how it is that these different kinds of research fit together to provide us with the science and understanding necessary to make clinical and public health decisions. Now typically, people tend to think of research methods in terms of qualitative research and quantitative research, and they're these two distinct disciplines or two distinct types of research methods, and the qualitative research is the domain of the social scientists and anthropologists, and the quantitative research is the domain of the epidemiologists and economists. And what I'd like to talk to you a little bit about is the fact that these two groups of people actually use both sets of research methods. So let's just jump right in and try and understand these different research techniques and research methods. Qualitative research tends to answer questions like who, what, why, when, and how. It tries to unpack and understand the nature of a phenomenon or the qualities associated with a particular phenomenon. By contrast, quantitative research answers the question of how much. It considers the idea of magnitude. So when we're talking about magnitude, the how much, the quantitative research, we're talking about the how much of, firstly, an occurrence, so the incidence or prevalence of a disease in a community, and we're talking about the magnitude or the how much of a relationship, so the association, for example, between a risk factor and an outcome. So now I'm just going to quickly give you an overview of some of the research methods used in these two groups of methods, qualitative research and quantitative research. In qualitative research, we may do a simple observation of what's happening in a community or you might be looking down a microscope, for example, that's qualitative research. We may do in-depth interviews or key informant interviews. We may do focus groups and speak to a group of people. We may do surveys. All of this is to try and unpack and understand the underlying nature or qualities within a phenomenon. The other group, the quantitative research, now we've got interventional quantitative research and we've got non-interventional. By non-interventional, we mean it's observational. We're watching to see what happens in the world and we're counting something up. So in that sense, we might be doing case control studies and we'll talk more about that in a future video. We may be doing cohort studies and I'm specifically going to talk in a future video about the difference between those two and their relative strengths and weaknesses. We may do an ecological study and we may, of course, also be doing a survey and just collecting data in that sense. Then of course, there's the interventional trials and the one we talk about most are randomized control trials or double-blind randomized control trials. We're going to do an entire video that looks specifically at that. Okay, thanks for listening. I hope that was helpful. This was just a synopsis, an overview of the various research methods that we use. In future videos, we're going to dig down a little deeper and look at some of the details of these different study designs and research methods that get used. If you're thinking of subscribing to this channel, let me give you one or two reasons why I think that's a great idea. Firstly, if you subscribe to the channel, you get an email alert whenever there's a new video posted and so you'll be up to date on the things that we say and do here on the channel. But secondly, I send out video content that goes exclusively to people who subscribe to this channel. I think of the people who subscribe to the channel as a subset of the broader audience and they're more likely to be people that are interested in job opportunities in the global health space and where it is that they might find opportunities to do consulting work in global health. I'm putting together, they're a little less formal, they're a little less flashy, but videos that just kind of talk people through what's out there and what's happening in the global health workspace. Subscribe to the channel. Thanks for watching. I'll be back.

Strengths and Limitations of Qualitative and Quantitative Research Methods

• September 2017
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• Instituto Superior Politécnico Gaya
• This person is not on ResearchGate, or hasn't claimed this research yet.

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