business statistics assignment sample

BUS204: Business Statistics

Course introduction.

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Here, we will look at summary statistics, which give an overview of a data set, such as the average score on an exam. However, the average does not always tell the entire story; since half of the students could have gotten 100 on the exam, and the other half gotten 60. Using statistics, we can learn a lot more about how data is organized. To do that, we will use statistical tools to analyze data, draw conclusions, and make predictions about the future. The course will begin with data distributions, followed by probability analysis, sampling, hypothesis testing, inferential statistics, and regression.

Course Syllabus

First, read the course syllabus. Then, enroll in the course by clicking "Enroll me". Click Unit 1 to read its introduction and learning outcomes. You will then see the learning materials and instructions on how to use them.

Unit 1: Introduction to Statistical Analysis

Even if you haven't taken a statistics course before, you are already familiar with the fundamentals of statistics from your everyday life. For instance, you already know that the majority of adult males have the same shoe size (which is very close to the average size), and that there are a few adult males on both sides of the average who have smaller or larger shoe sizes. In statistics, we call this phenomenon the "normal distribution".

This unit will introduce you to statistical analysis and how it relates to business. For example, you may be interested in learning about the average price of a 50-inch TV by gathering price data from 30 different stores. You would then take your 30 prices and compute the average price. Given the fact that there are thousands of stores that are selling that particular product, the next question in statistics is: are you confident enough to say that your computed average is reflective of the real average that you would get if you looked at the price for that TV at every possible store?

You are probably familiar with the average of a data set. In this course, we will refer to what most people call the average as the "arithmetic mean". The average is actually any single value used to describe the middle of a data set. The most common averages used in statistics are the arithmetic mean, the median, and the mode. Each describes the middle of a dataset in different ways. The median is the numeric value that separates the upper and lower half of a data set. The mean is the sum of all values divided by the number of values. The mode is the most common value within the dataset.

In many instances, the median and the mean are similar, but we will also talk about many examples where it is not. The distinction between these kinds of summary statistics is important in business statistics. Understanding this vocabulary will be vital to your success in this course and in the business world.

Completing this unit should take you approximately 6 hours.

Unit 2: Counting, Probability, and Probability Distributions

How likely is it that a certain event will occur? What are the chances that a given student will receive a grade of 60–69 on their exam? By studying distributions of data, you can determine the probability that a certain event will occur. By looking at the distribution of grades in a class, you can identify the probability that a student will receive between a 60 and 69. Probability is used in business to predicting profits, determine the chances that a business model will affect regulation, and in many other ways.

Before you can focus on probability, you must first learn how to count. What's that? You already know how to count? Maybe – but in this unit, you will learn how to count the different ways that multiple events can occur together. These are called combinations and permutations , and they are a fundamental concept of probability.

Completing this unit should take you approximately 12 hours.

Unit 3: The Normal Distribution

A distribution is a line graph representation of the probability that an event will occur. It is similar to a histogram, but in a distribution, the user does not determine the grouping; instead, data is grouped according to the likelihood that it will occur within the data set. Distributions also allow for analysis of a specific event, whereas a histogram requires events be grouped.

An important type of this distribution is the "normal" distribution. The normal distribution is used to approximate real-world occurrences. If you can make certain assumptions about the occurrence of an event, then you can use the normal distribution to find out the probabilities of that event occurring. Many of the events that are important to business can be approximated using the normal distribution.

Completing this unit should take you approximately 3 hours.

Unit 4: Sampling and Sampling Distributions

While you may not become a professional data gatherer, it is likely that you will need to compile data on a regular basis. When gathering data, you will not always have the luxury of collecting all available data. For example, economists cannot measure the entire unemployment of the population, so they must take a random sample instead. Likewise, in a manufacturing facility, quality control managers do not have the resources to test every product that comes off the line; it is simply not feasible. Instead, they take samples at various points during the production process to test the quality of the products the firm produces.

There are a number of methods employed in sampling data. It is important that the sampling method fits the application. For example, marketing managers may wish to test a product on various groups of people. They may define these groups by age, race, geography, income, or any other factors. They then divide the population into these groups and take samples from each group in a process known as cluster sampling. If marketers do not properly divide the population, they may end up marketing to the wrong demographic and achieving poor sales.

Unit 5: Estimation and Hypothesis Testing

Estimation is the process of making predictions based on the best available information. Businesses employ estimation in order to help managers make decisions regarding the future. For example, if the CFO estimates profits will be lower next year, the CEO will consider cost-cutting measures to make up for the loss. Normally, companies do not want to pursue aggressive cost-cutting because it usually comes in the form of layoffs, which are bad for employee morale.

In order to make accurate estimates, companies use hypothesis testing. For example, assume the CFO thinks profits will be below 5% of revenue next year. His null hypothesis is that profits will be 5% or greater next year. The alternative hypothesis is that profits will not be 5% or greater next year. This seems counter-intuitive, but statistics proposes that a hypothesis cannot be proven true; it can only be rejected, or shown to be not true. Through the hypothesis testing process, the CFO will either reject or accept the null hypothesis. Hypothesis tests are always framed in this manner because, with imperfect information, nothing can be proven. 

The best non-business analogy to hypothesis testing comes from the courtroom. In the United States, a defendant is presumed innocent until proven guilty. The null hypothesis in this scenario is innocent or not guilty. The alternative hypothesis is guilty. In order to find the defendant guilty, the jury must be offered enough evidence that suggests the defendant is guilty beyond a reasonable doubt. If the members of the jury make that decision, then they reject the null hypothesis. If the jury members decide they do not have enough evidence to make that judgment, then they must find the defendant not guilty. Notice not guilty does not mean the jury claims the defendant is innocent. The decision simply means the members of the jury do not have enough information to find the person guilty, so they err on the side of caution and fail to reject the null hypothesis. As an aside, in this example, beyond a reasonable doubt is analogous to the level of significance, which you will learn is crucial to hypothesis testing.

Completing this unit should take you approximately 11 hours.

Unit 6: Correlation and Regression

If two data points move in the same direction, does that mean that one causes the other? How are we to analyze their correlation?

Regression is an analysis of the relationship of one variable to another. A regression might identify, for example, the relationship between car speed and the number of fatal accidents. In this example, speed and number of accidents are the two variables; the number of accidents is said to be the dependent variable, because the number of accidents depends on the speed. Speed is considered the independent variable. While regressions can be calculated manually, a statistically significant data set could take a long time to regress.

Regressions not only allow us to determine whether a relationship exists but also to identify how strong that relationship is. The measure of this relationship is known as the regression coefficient. If the regression coefficient is relatively low, then speed may not be the major factor in fatal accidents. Perhaps the major factor is the time of day, whether it rained or not, or if alcohol was involved. With multiple regression, a number of independent variables can be tested against the dependent variable at the same time. The regression coefficient would determine which variables have the strongest relationship with the dependent variable. In business, you will frequently use regression to predict future events. Though not an exact science, regression can be used to make reliable predictions if enough variables are identified. For example, first responders could use regression outputs to predict the number of fatal accidents in a given shift based on average travel speed, time of day, weather, and any other factors deemed significant. This unit will also stress the importance of determining the factors that most likely contribute to a dependent variable. 

Regression is often used in finance. Investors often want to know the relationship between a stock's performance and the overall performance of the market. By regressing the period returns of a stock with the returns of the market, investors can see the regression coefficient. This coefficient is known as a stock's beta and is covered extensively in BUS202: Principles of Finance .

Completing this unit should take you approximately 5 hours.

Study Guide

This study guide will help you get ready for the final exam. It discusses the key topics in each unit, walks through the learning outcomes, and lists important vocabulary. It is not meant to replace the course materials!

Course Feedback Survey

Please take a few minutes to give us feedback about this course. We appreciate your feedback, whether you completed the whole course or even just a few resources. Your feedback will help us make our courses better, and we use your feedback each time we make updates to our courses.

If you come across any urgent problems, email [email protected].

Certificate Final Exam

Take this exam if you want to earn a free Course Completion Certificate.

To receive a free Course Completion Certificate, you will need to earn a grade of 70% or higher on this final exam. Your grade for the exam will be calculated as soon as you complete it. If you do not pass the exam on your first try, you can take it again as many times as you want, with a 7-day waiting period between each attempt.

Once you pass this final exam, you will be awarded a free Course Completion Certificate .

Saylor Direct Credit

Take this exam if you want to earn college credit for this course . This course is eligible for college credit through Saylor Academy's Saylor Direct Credit Program .

The Saylor Direct Credit Final Exam requires a proctoring fee of $5 . To pass this course and earn a Credly Badge and official transcript , you will need to earn a grade of 70% or higher on the Saylor Direct Credit Final Exam. Your grade for this exam will be calculated as soon as you complete it. If you do not pass the exam on your first try, you can take it again a maximum of 3 times , with a 14-day waiting period between each attempt.

We are partnering with SmarterProctoring to help make the proctoring fee more affordable. We will be recording you, your screen, and the audio in your room during the exam. This is an automated proctoring service, but no decisions are automated; recordings are only viewed by our staff with the purpose of making sure it is you taking the exam and verifying any questions about exam integrity. We understand that there are challenges with learning at home - we won't invalidate your exam just because your child ran into the room!

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Once you pass this final exam, you will be awarded a Credly Badge and can request an official transcript .

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4 Examples of Business Analytics in Action

• 15 Jan 2019

Data is a valuable resource in today’s ever-changing marketplace. For business professionals, knowing how to interpret and communicate data is an indispensable skill that can inform sound decision-making.

“The ability to bring data-driven insights into decision-making is extremely powerful—all the more so given all the companies that can’t hire enough people who have these capabilities,” says Harvard Business School Professor Jan Hammond , who teaches the online course Business Analytics . “It’s the way the world is going.”

Before taking a look at how some companies are harnessing the power of data, it’s important to have a baseline understanding of what the term “business analytics” means.

Access your free e-book today.

What Is Business Analytics?

Business analytics is the use of math and statistics to collect, analyze, and interpret data to make better business decisions.

There are four key types of business analytics: descriptive, predictive, diagnostic, and prescriptive. Descriptive analytics is the interpretation of historical data to identify trends and patterns, while predictive analytics centers on taking that information and using it to forecast future outcomes. Diagnostic analytics can be used to identify the root cause of a problem. In the case of prescriptive analytics , testing and other techniques are employed to determine which outcome will yield the best result in a given scenario.

Related : 4 Types of Data Analytics to Improve Decision-Making

Across industries, these data-driven approaches have been employed by professionals to make informed business decisions and attain organizational success.

Check out the video below to learn more about business analytics, and subscribe to our YouTube channel for more explainer content!

Business Analytics vs. Data Science

It’s important to highlight the difference between business analytics and data science . While both processes use big data to solve business problems they’re separate fields.

The main goal of business analytics is to extract meaningful insights from data to guide organizational decisions, while data science is focused on turning raw data into meaningful conclusions through using algorithms and statistical models. Business analysts participate in tasks such as budgeting, forecasting, and product development, while data scientists focus on data wrangling , programming, and statistical modeling.

While they consist of different functions and processes, business analytics and data science are both vital to today’s organizations. Here are four examples of how organizations are using business analytics to their benefit.

Business Analytics Examples

According to a recent survey by McKinsey , an increasing share of organizations report using analytics to generate growth. Here’s a look at how four companies are aligning with that trend and applying data insights to their decision-making processes.

1. Improving Productivity and Collaboration at Microsoft

At technology giant Microsoft , collaboration is key to a productive, innovative work environment. Following a 2015 move of its engineering group's offices, the company sought to understand how fostering face-to-face interactions among staff could boost employee performance and save money.

Microsoft’s Workplace Analytics team hypothesized that moving the 1,200-person group from five buildings to four could improve collaboration by increasing the number of employees per building and reducing the distance that staff needed to travel for meetings. This assumption was partially based on an earlier study by Microsoft , which found that people are more likely to collaborate when they’re more closely located to one another.

In an article for the Harvard Business Review , the company’s analytics team shared the outcomes they observed as a result of the relocation. Through looking at metadata attached to employee calendars, the team found that the move resulted in a 46 percent decrease in meeting travel time. This translated into a combined 100 hours saved per week across all relocated staff members and an estimated savings of $520,000 per year in employee time.

The results also showed that teams were meeting more often due to being in closer proximity, with the average number of weekly meetings per person increasing from 14 to 18. In addition, the average duration of meetings slightly declined, from 0.85 hours to 0.77 hours. These findings signaled that the relocation both improved collaboration among employees and increased operational efficiency.

For Microsoft, the insights gleaned from this analysis underscored the importance of in-person interactions and helped the company understand how thoughtful planning of employee workspaces could lead to significant time and cost savings.

2. Enhancing Customer Support at Uber

Ensuring a quality user experience is a top priority for ride-hailing company Uber. To streamline its customer service capabilities, the company developed a Customer Obsession Ticket Assistant (COTA) in early 2018—a tool that uses machine learning and natural language processing to help agents improve their speed and accuracy when responding to support tickets.

COTA’s implementation delivered positive results. The tool reduced ticket resolution time by 10 percent, and its success prompted the Uber Engineering team to explore how it could be improved.

For the second iteration of the product, COTA v2, the team focused on integrating a deep learning architecture that could scale as the company grew. Before rolling out the update, Uber turned to A/B testing —a method of comparing the outcomes of two different choices (in this case, COTA v1 and COTA v2)—to validate the upgraded tool’s performance.

Preceding the A/B test was an A/A test, during which both a control group and a treatment group used the first version of COTA for one week. The treatment group was then given access to COTA v2 to kick off the A/B testing phase, which lasted for one month.

At the conclusion of testing, it was found that there was a nearly seven percent relative reduction in average handle time per ticket for the treatment group during the A/B phase, indicating that the use of COTA v2 led to faster service and more accurate resolution recommendations. The results also showed that customer satisfaction scores slightly improved as a result of using COTA v2.

With the use of A/B testing, Uber determined that implementing COTA v2 would not only improve customer service, but save millions of dollars by streamlining its ticket resolution process.

Related : How to Analyze a Dataset: 6 Steps

3. Forecasting Orders and Recipes at Blue Apron

For meal kit delivery service Blue Apron, understanding customer behavior and preferences is vitally important to its success. Each week, the company presents subscribers with a fixed menu of meals available for purchase and employs predictive analytics to forecast demand , with the aim of using data to avoid product spoilage and fulfill orders.

To arrive at these predictions, Blue Apron uses algorithms that take several variables into account, which typically fall into three categories: customer-related features, recipe-related features, and seasonality features. Customer-related features describe historical data that depicts a given user’s order frequency, while recipe-related features focus on a subscriber’s past recipe preferences, allowing the company to infer which upcoming meals they’re likely to order. In the case of seasonality features, purchasing patterns are examined to determine when order rates may be higher or lower, depending on the time of year.

Through regression analysis—a statistical method used to examine the relationship between variables—Blue Apron’s engineering team has successfully measured the precision of its forecasting models. The team reports that, overall, the root-mean-square error—the difference between predicted and observed values—of their projection of future orders is consistently less than six percent, indicating a high level of forecasting accuracy.

By employing predictive analytics to better understand customers, Blue Apron has improved its user experience, identified how subscriber tastes change over time, and recognized how shifting preferences are impacted by recipe offerings.

Related : 5 Business Analytics Skills for Professionals

4. Targeting Consumers at PepsiCo

Consumers are crucial to the success of multinational food and beverage company PepsiCo. The company supplies retailers in more than 200 countries worldwide , serving a billion customers every day. To ensure the right quantities and types of products are available to consumers in certain locations, PepsiCo uses big data and predictive analytics.

PepsiCo created a cloud-based data and analytics platform called Pep Worx to make more informed decisions regarding product merchandising. With Pep Worx, the company identifies shoppers in the United States who are likely to be highly interested in a specific PepsiCo brand or product.

For example, Pep Worx enabled PepsiCo to distinguish 24 million households from its dataset of 110 million US households that would be most likely to be interested in Quaker Overnight Oats. The company then identified specific retailers that these households might shop at and targeted their unique audiences. Ultimately, these customers drove 80 percent of the product’s sales growth in its first 12 months after launch.

PepsiCo’s analysis of consumer data is a prime example of how data-driven decision-making can help today’s organizations maximize profits.

Developing a Data Mindset

As these companies illustrate, analytics can be a powerful tool for organizations seeking to grow and improve their services and operations. At the individual level, a deep understanding of data can not only lead to better decision-making, but career advancement and recognition in the workplace.

“Using data analytics is a very effective way to have influence in an organization,” Hammond says . “If you’re able to go into a meeting, and other people have opinions, but you have data to support your arguments and your recommendations, you’re going to be influential.”

Do you want to leverage the power of data within your organization? Explore Business Analytics —one of our online business essentials courses —to learn how to use data analysis to solve business problems.

This post was updated on March 24, 2023. It was originally published on January 15, 2019.

About the Author

MR. NELSON'S BUSINESS STATISTICS

Andrew Nelson of Granada Hills Charter High School Presents

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• FALL 2020 STUDY MATERIALS

BUSINESS STATISTICS

• AP CAPSTONE
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Welcome - Class Rules - Class Overview

Syllabus Download

Knowledge Matters Account Creation

Introduction To Financial Functions

Asychronous Assignments Week #1 - Due August __, 2020

Knowledge Matters Accounting Lesson #1:  “ T-Accounts, Debits & Credits "

Practice Financial Functions Practice Test #A1

Practice Financial Functions Test #A1 Annotated Answers

Practice Financial Functions Test #A1 Answers PDF Format

Practice Financial Functions Practice Test #A2

Practice Financial Functions Test #A2 Annotated Answers

Practice Financial Functions Test #A2 Answers PDF Format

Asychronous Assignments Week  #2  - Due August __, 2020

Knowledge Matters Accounting Lesson #2:  “Using A General Journal "

Knowledge Matters Accounting Lesson #3:  “The General Ledger ”

DECA DAY #1 - Chapter Elections

WEEK THREE: 

Asychronous Assignments Week  #3  - Due September __, 2020

Knowledge Matters Accounting Lesson #4:  “Worksheet & the Accounting Cycle "

Knowledge Matters Accounting Lesson #5:  “Analyzing Financial Statements ”

Asychronous Assignments Week  #4  - Due September __, 2020

Knowledge Matters Accounting Lesson #6:  “Managerial Accounting I "

Knowledge Matters Accounting Lesson #7:  “Managerial Accounting II "

DECA DAY #2 - Chapter Campagns

WEEK FIVE: 

Asychronous Assignments Week  #5  - Due September __, 2020

Knowledge Matters Accounting Lesson #8:  “Ratio Analysis "

Knowledge Matters Accounting Lesson #9:  “Forensic Accounting Challenge I "

Asychronous Assignments Week  #6  - Due September __, 2020

Knowledge Matters Accounting Lesson #10:  “Forensic Accounting Challenge II "

Knowledge Matters Accounting Lesson #11:  “Forensic Accounting Challenge III "

DECA DAY #3 - DECA Stock Market Game

WEEK SEVEN:

Asychronous Assignments Week  #7  - Due October __, 2020

LAUNCH -  GUIDED INSTRUCTIONAL PLAN

MAKE-UP FINAL EXAM & PREPARATION MATERIALS

Knowledge Matters Hotel Cumulative Assessment = Socrative Room  GHCDF 2

 Buy A Bond Unit Assessment = Socrative Room  GHCDF 1

FINAL EXAM & PREPARATION MATERIALS

The final is comprised of two parts - Knowledge Matters Hotel Cumulative Assessment and Buy A Bond Unit Assessment .  Both exams are Socrative - mostly multiple choice with some true/false.  These exact questions have all been previously addressed in Zoom lectures and/or in asynchronous lesson materials.  To study for the exam, go to the following Socrative rooms.

Knowledge Matters Hotel Cumulative Assessment = Socrative Room 

 Buy A Bond Unit Assessment = Socrative Room 

Attendance at the final exam is mandatory.  Students failing to take the final assessments will receive an NTI for both exams (counts as a zero in the grade calculation.)  Together, these exams will account for about 5% of the student’s overall grade percentage. Students will take these exams during their live session as scheduled below. If you cannot attend class that day and/or time, please contact Mr. Nelson in advance. Expect make-up times will be scheduled between 7-8am on the remaining days of finals week.

Period Two Business Statistics Final

Wednesday June 3 - 10:30am-11:30am.

Period Three & Four Business Statistics Finals    

Wednesday June 3 - 11:30am-12:30pm.

MAKE-UP Socrative Rooms Now Posted For Assignments Originally Due April 18 - May 22.  Final school due date is May 29.

LinkedIn Lesson #4 = Socrative Room  GHCDH3

  READ Pages 18-37 From This Link     Use LinkedIn To Get Into Your Dream College       Then Complete Socrative Exit Survey

Career 123 Personality Test = Socrative  Room  GHCDH 1

Complete this career personality test    123 Career Test     Then Complete Socrative Exit Survey  

Knowledge Matters Hotel Simulation Lessons #8-10 plus 3 Hours Hotel Mogul Sim Active Engagement

LIVE SESSION: Wednesday, May 20 - Buy A Bond Unit Part Three

Go to Socrative Room  GHCDF2  to complete the exit quiz.  Note that this quiz will be retaken as part of the final exam.

Previous Class Videos For Your Review:   Bond Ladders   &   Yield To Worst Video  

Coming Soon:   “We’re All Data Scientists ”      Jose Andres’ GWU Graduation Address

REMOTE INSTRUCTION WEEK #9

Asynchronous Assignments:   Three More Career Surveys To Complete - Note that Week #10 will be devoted to study time for the final (scheduled for June 1-5), and to completing remaining make-up work including this week’s assignments.

#1 - Complete  The TypeFinder for Career Planning  Assessment

Then Record Your Results in the assigned Socrative Room

Periods One & Two - SOCRATIVE ROOM GHCDP1

Periods Three & Four - SOCRATIVE ROOM GHCDP2 

#2 - Complete Career Personality Profiler Assessment

Periods One & Two - SOCRATIVE ROOM GHCDP3

Periods Three & Four - SOCRATIVE ROOM GHCDP4 

#3 - Complete Photo Career Quiz Assessment

Periods One & Two - SOCRATIVE ROOM GHCDF3

Periods Three & Four - SOCRATIVE ROOM GHCDF4 

Please Review the GHC LATE WORK POLICY

Due May 22, 2020:  Students will be able to submit work which was due between March 16 and April 17 . Students are able to earn full credit based on criteria met and successful completion of the assignment. Students are still held to the GHC Integrity Policy.

Due May 29, 2020: Students will be able to submit work due between April 20 and May 19 . Students are able to earn full credit based on criteria met and successful completion of the assignment. Students are still held to the GHC Integrity Policy.

Work assigned after May 19, 2020 must be on time for students to earn full credit based on criteria met and successful completion of the assignment.

Socrative Rooms & LinkedIn Reading Materials for Make-up - Pre-April 17:  Note that Socrative room limits will require me to take these tests down after May 22.   Make-up Socrative rooms for  assignments given from April 20-May 19 will be posted on May 23.  Socrative only provides 10 rooms per account which necessitates this rotation.

LinkedIn Lesson #1 = Must contact Mr. Nelson for exception

READ This Link   LinkedIn Profile Checklist for High School Students   Then Complete Socrative Exit Survey

LinkedIn Lesson #2 =Must contact Mr. Nelson for exception

READ These Two Links   LinkedIn Tip Sheet - How to Communicate Effectively On LinkedIn        

LinkedIn Tip Sheet - Building Your Personal Brand    Then Complete Socrative Exit Survey

LinkedIn Lesson #3 = Must contact Mr. Nelson for exception

READ These Three Links    LinkedIn Tip Sheet - Tailoring Your Profile To Meet Your Goals

LinkedIn Tip Sheet - How to Communicate Effectively on LinkedIn

LinkedIn Tip Sheet - Alumni Tool     Then Complete Socrative Exit Survey

LIVE SESSION: Monday, May 11 - Buy A Bond Lesson - Part Two

CLASS VIDEOS:   Bond Ladders   &   Yield To Worst Video - SOCRATIVE EXIT QUIZ

REMOTE INSTRUCTION WEEK #8

Asynchronous Assignment:   Knowledge Matters  “Hotel Mogul Project”

Run the Hotel Simulation for Three Hours &

Then “SUBMIT" Your Progress By  Friday, May 15  11:59pm (midnight)

All will compete but who will WIN? Big Point Bonuses For The Top Performers!!

Once you have spent three hours running the Hotel Simulation, you should submit your simulation results - even if you have not reached the 85 Balanced Scorecard Goal . The Knowledge Matters softward allows teachers to see every click or lack of click you make (pretty sophisticated stuff).  So please don’t try to fake it by just logging in as that will only show three hours with no activity or setting changes - that will earn no points.  In addition, each of your simulation runs are saved in the system for teachers to review. 

Grades will be assigned based on the following metrics.  

BE ACTIVELY ENGAGED IN MAKING ADJUSTMENTS TO THE SETTINGS IN  Actions>>   - Many rounds of trial and error

RUN THE HOTEL SIMULATION MANY TIMES TO SEE HOW THOSE SETTING CHANGES PERFORM  

Here’s a quick preview of the Hotel Simulation tasks. Refer to the lesson simulations for additional guidance on how to adjust simulation settings.

STEP ONE: In this Hotel simulation, you will manage all aspects of the hotel including:

• Restaurant Operations
• Banquet and Meeting Operations
• Housekeeping
• Group Sales Bids

Your hotel is just opening and will need to have all aspects of its operations set up.  Most settings are under the "Actions” tab in the upper right hand corner of the window ( Actions>>) .  If you encounter trouble setting up some elements of the hotel, don’t worry about it - just do your best for three hours, and have some fun seeing what you can get to work.  YOU CAN'T BREAK IT!! GO FOR IT!!

If you find these Simulation exercises difficult, then consider setting up just the restaurant and front desk staffing first. Setting the menu pricing for the restaurant and using their scheduler tool are two of the more intuitive features.  Then run the simualtion and see how you do.  Again BE AGGRESSIVE at making changes.   

STEP TWO: You should refer to the  Actions>> " Market Data Report"  to determine the characteristics of the demand for your hotel. This report includes data that can help your decision making in both your lodging operations and your food and beverage operations.

In this project, you may run the simulation for long enough to take advantage of the seasonal trends in the hotel industry. Information is as seen in the " Group Demand Seasonal Trends"  graph on the  Actions>> " Market Data Report" . As well, you can refer to the special events listed on the  Actions>>"Front Desk"  calendar month by month to determine your busy season for special events.

LIVE SESSION: Wednesday, May 6 - Buy A Bond Lesson - Part One 

CLASS VIDEOS: Go to Google Classroom to view the recording of today’s lesson on purchasing  bonds.  No follow-up Socrative exit quiz today.

ALTERNATE ASSIGNMENT: DUE Friday, May 15 11:59PM 

Instructions & Format Requirements - LinkedIn Profile Alternate Assignment

Here are the instructions for the LinkedIn Profile alternate assignment .  I recorded EXT (extended time) for anyone who did not create a LinkedIn profile.  Whether you requested the alternate or not, I gave you EXT so it would not negatively influence your R5 grade.  Anyone with an EXT must complete the alternate assignment by Friday May 15 or the score will revert to an NTI (same as any work granted "extended time").  Let me know if you need any further direction or clarification.  

LIVE SESSION: Monday, May 4 

CLASS VIDEOS:   Investing Basics: Bonds  (3:55)   AND  Shedding Light on the Bond Buying Porcess - Isn’t It Time  (4:40)

The exit quiz has been pulled down to open up needed Socrative rooms.  Contact Mr. Nelson to arrange access.

MAKE-UP Past Missed LinkedIn Assignments (Email Mr. Nelson when done and he’ll update the grade book.)

LINKEDIN LESSON #1 - READ This Link  

LinkedIn Profile Checklist for High School Students   

Then complete the exit quiz.  contact Mr. Nelson for SOCRATIVE ROOM.

LINKEDIN LESSON #2 - READ These Two Links

LinkedIn Tip Sheet - How to Communicate Effectively On LinkedIn

LinkedIn Tip Sheet - Building Your Personal Brand

Then complete the exit quiz. . SOCRATIVE ROOM GHCDP2 = LinkedIn Lesson #2

LINKEDIN LESSON #3 - READ These Three Links

LinkedIn Tip Sheet - Tailoring Your Profile To Meet Your Goals

LinkedIn Tip Sheet - Alumni Tool    

Then complete the exit quiz.  SOCRATIVE ROOM GHCDP3 =  LinkedIn Lesson #3

LINKEDIN LESSON #4 - READ   Use LinkedIn To Get Into Your Dream College   

Pages 18-37,  How to Create and Optimize Your LinkedIn Profile Items #1-7  

Then complete the exit quiz.   SOCRATIVE ROOM GHCDP4 = LinkedIn Lesson #4 

REMOTE INSTRUCTION WEEK #7

Complete The Last Knowledge Matters Lesson 

“Monitoring Competitors” 

Due Friday, May 8  11:59pm (midnight)

Students Take the 123 Career Test

Then Complete A Socrative Follow-up Survey

Period Two - SOCRATIVE ROOM  

Period Three - SOCRATIVE ROOM  

Period Four - SOCRATIVE ROOM  

FUTURE READING ASSIGNMENTS LinkedIn - From Profile to Job Seeker

LinkedIn Job Seeker Part #1

LinkedIn Job Seeker Part #2

LinkedIn Job Seeker Part #3

*********************************************************************************

PAST ASSIGNMENTS LISTED BELOW

LIVE SESSION: Wednesday, April 29

CLASS VIDEO:   Can data tracking curtail the Coronavirus pandemic?   

Go to Socrative Room ***** Complete Follow-up Survey For This Lesson

LIVE SESSION: Monday, April 27

CLASS VIDEO:   The Computer Algorithm that was among the first to detect Coronavirus

LIVE SESSION: Wednesday, April 22   

CLASS VIDEO:  Mathematics of Epidemics | Trish Campbell | TEDxYouth@Frankston    Bill Gates March 2015

REMOTE INSTRUCTION WEEK #6

Complete One Knowledge Matters Lesson 

“Financial Reports” 

Due Friday, May 1  11:59pm (midnight)

LinkedIn Lesson #5 -   Students Finish Their LinkedIn Profile

   Use LinkedIn To Get Into Your Dream College   

R ead Pages 37-50,  How to Create and Optimize Your LinkedIn Profile Items #8-16

Student Profile Due Friday, May 1  11:59pm (midnight)

REMOTE INSTRUCTION WEEK #5

Complete One Knowledge Matters Lesson  

“Operations: Housekeeping”

Due Friday, April 24  11:59pm (midnight)

LinkedIn Lesson #4 - Students Begin To Create Their Own LinkedIn Profile

R ead Pages 18-37,  How to Create and Optimize Your LinkedIn Profile Items #1-7

Complete Socrative Reading Quiz Due Friday April 24  11:59PM

REMOTE INSTRUCTION WEEK #4

  Live Session #1 - Monday April 13, 2o2o

REVIEW - Presentation Slides April 13 Live Session

VIDEO #1 -  Start Your Career - LinkedIn For Students

VIDEO #2 - LinkedIn For Students Top Five Profile To Dos

VIDEO #3 - LinkedIn Community: A Superpower Hiding in Plain Sight   (Sandra Long 5/19)

SOCRATIVE ROOMS - Socrative windows will be opened 15 minutes into each session.

Period Two - Complee culminating activity in room ****

Period Three  - Complee culminating activity in room ***

Period Four  - Complee culminating activity in room ****

See Official GHC Schedule Below For Live Session Times - Mr. Nelson Classes  

THIS WEEK’S ASYNCHRONOUS ASSIGNMENTS

Complete Two Knowledge Matters Lessons 

“Operations: Restaurant & Culinary”  &  “Operations: Banquets & Meetings" 

Both Due Friday, April 17  11:59pm (midnight)

LinkedIn Lesson #3 - Refining Your LinkedIn Profile

READ  these 3 LinkedIn Reading Assignments

LinkedIn Tip Sheet - Alumni Tool

THEN PROCEED TO SOCRATIVE SELF ASSESSMENT GUIDE -  Go to the appropriate Socrative room (socrative.com) and complete the multiple choice and free response questions.   This assignment will be due Friday April 17 11:59pm.

LinkedIn Lesson #6 - From Profile to Job Seeker

LAUNCH  -  GUIDED INSTRUCTIONAL PLAN OVERVIEW

Largely A Repost of Email Sent Friday April 3

. . . The following paragraphs will share what you need to know as we prepare for a more structured schedule when school returns from spring break. Please read the entire email carefully. You need this information . The last section addresses some student inquiries regarding LinkedIn lesson #2. Try to enjoy your indoor spring breaks as much as possible, and BE SAFE! Mr. Nelson Spring Break : No change here. No work will be assigned over spring break next week. We return to school on Monday April 13. Make-up Opportunity For Work Missed In The First 3 Weeks of Remote Instruction: Given the circumstances, I am allowing all students to make-up work missed during the first three weeks of remote instruction. Knowledge Matters allows you access to these lessons at any time. Go to Socrative room 'GHCDP1' for making up the first LinkedIn lesson.  For the second LinkedIn assignment, go to Socrative room 'GHCDF2’ for period two, ‘GHCDF3” for period three and ‘GHCDF4’ for period four - all will remain open over break for those students who need to make up that work. Please email me when you submit this make-up work so I know to update your grade. Quick Note To Seniors: Most of our second period are seniors, and I feel bad for you all being robbed of your grand finales in secondary education. It will give you something to tell to your grandchildren about. And know that you will tell your grandchildren about this event and your experiences living through it. As an aside (not a class requirement), I encourage you to keep a diary of thoughts as we go through the coming weeks. In some way record your thoughts to share with future generations. Trust me your memories will not be as strong when you have grandchildren (observation of an old guy). LAUNCH Guided Instructional Plan: The school will be sending "big picture" details soon but here's an outline of what Business Statistics will look like after break. Preview of Mandatory Live Instruction: Here's the big change for us. GHC will require every class to have two live class sessions of twenty minutes each;  Expect these sessions will involve: (1) a five-minute welcome including a review of student protocol and student question time; (2) a lecture or video of about 10-12 minutes; and (3) a short teacher wrap-up that will provide another opportunity to ask questions. Most of the sessions will have a Socrative based follow-up assignment. That assignment will count toward the three hour asynchronous (independent) work requirement. More details on student expectations for these live sessions will be shared during break. 

PLEASE NOTE THE SLIGHT CHANGE IN TIMES BELOW (This schedule aligns with the published schedule below.) Period two Buisness Statistics sessions will start at 3:00pm on Mondays and 11:00am on Wednesdays. 

Period three Business Statistics sessions will start at 3:30pm on Mondays and 11:30am on Wednesdays. Period four Business Statistics sessions will start at 4:00pm on Mondays and 12:00pm (noon) on Wednesdays.

Asynchronous (aka Independent) Assignments After Spring Break: Knowledge Matters has been working well for the class. That was expected given our past experience with KM and that it's designed for remote instruction. I will continue to emphasize these highly refined materials that are designed for this form of instructional delivery. The other independent work will digest reading and video materials followed by student checks for understanding and personal reflections delivered through the Socrative platform. Let me thank everyone for your flexibility in working with the Socrative assignments so far. The Socrative based lessons were not designed to be given at home. That's a byproduct of eliminating homework from Business Statistics a few years ago. The class at large has been handling them well, and when you've encountered issues that needed clarity you've contacted me by email. Keep that up and all will continue to turn out well. The live sessions will give you an opportunity to get clarifications on future Socrative assignments (in addition to email). Due Dates: No change here. Flexibility continues to be the theme. Just continue to email me when you need additional time on any assignment or if you are unable to attend one of the live sessions. Length of Time To Complete Independent Assignments: The "asynchronous" (aka independent) instructional time of three hours will not change. Previously, I've sought to assign work that has meaning for you but does not take more than three hours per week to complete (the mandated school standard) - that has not changed. Now we all know that no assignment takes everyone the same length of time to complete. It's a good example of spread in a distribution (remember "Center, Shape, Spread & Outliers"). As the teacher, do I consider that a minimum number of hours where few spend less than three hours? Do I consider that an average number of hours where half of the students spend more than three hours and half do more than three hours? Do I consider that a maximum number of hours where nearly all students spend less than three hours? Since the school has not clarified this requirement, I have consciously decided to go with the last interpretation given the unprecedented circumstances. Excel Applications & Certification: Not everyone has equal access to Excel at home so we will not be able to pursue more on this front. That does leave some holes in what I hoped we'd cover but there is no way to fill them this semester unfortunately. For any student who wishes to pursue Excel certification when we return to school (spring or fall), we can work out timing for practice and taking the test before school or during a regular period where your teacher would let you out of class. Seniors, you would be welcome to return to campus for this purpose as well. Note On Last Socrative Assignment: Several students had inquiries about the last Socrative assignment. Here's what helped to clarify that assignment for some. Multiple choice questions are covered in the assigned reading but free response questions are reflective questions that do not have right or wrong answers. They are intended to promote you reflecting on what you might put into your LinkedIn profile. Since it's a question about you, free response "answers" would not be found in the reading itself. Do your best to address the prompt with a well thought out paragraph. Do not spend more than ten-fifteen minutes on any single free response question (some could be done in less time). If you make an honest attempt to answer, you should get all the points. 

*************************************************************

ASSIGNMENTS - First Three Weeks of Remote Instruction

Week #3 (3/30-4/3, 2020) - Remote Learning Assignments

Greetings Business Statistics Periods 2-4 :

I hope you and your families are all safe and sound.  We enter the third week of remote instruction with some clearer direction and the knowledge that we will not return to the classroom in April.  Here’s the assignments for the coming week and a couple general announcements.

COMING ATTRACTION - LIVE INSTRUCTION!!   The school is establishing a more structured calendar for after Spring Break that will include a live (“synchronous”) instruction component  (likely two twenty-minute live class sessions per week per class).  To prepare us for the live (synchronous) instruction component, I will likely schedule a class session on Google Hangout or Zoom later this week.  This first session will focus on the digital logistics but it will also provide an opportunity to ask questions and get additional support.  If you have suggestions on how we might best use this time together, I’m all ears.  There is no precedence for what we’re doing here so all ideas are worth throwing out there.

AVAILABLE BY EMAIL EVERYDAY:   Email remains the quickest and most efficient means for us to communicate.  I am available most of the regular school day.  If you need me to be available in real time for more interactive communication, I’ve established "office hours”.   This week, you can reach to me Monday and Wednesday between 8:30-11:00pm.  I’m happy to schedule appointments in other windows of time as well.

GOOGLE CLASSROOM: With us not touching base everyday, I’ve decided to post assignments on Google classroom.  These instructions will be identical to those posted on the website and in the emails I send you.  Refer to my email today (Monday March 30) for the Google class code.

ASSIGNMENT GRADES ARE POSTED: Grades are posted for the first two weeks of remote instruction. If you see anything that’s not right, drop me an email and it’s easily corrected.  If you need an extension, just reach out and we’ll work around any limits you are encountering.  If you see NTI (“not turned in”), that indicates you didn’t complete the assignment and it counts the same as a “0”.  When people contact me and need additional time, I record EXT (“extended time”) until they are able to make up the work and this score designation does not impact the overall grade percentage.

WEEK #3 ASSIGNMENTS:  

“Customer Service: Front Desk” & “Customer Service: Social Media Feedback" 

One Due Wednesday, April 1  5:00pm   &   One Due Friday, April 3  5:00pm

Complete LinkedIn Lesson #2 Working With LinkedIn Profiles

Due Thursday, April 2  5:00pm 

Step #1 Read the two links below then keep these sources handy to help you answer the questions in Socrative.

(Contact Mr. Nelson if you encounter any download issues.)

STEP #2 SOCRATIVE SELF ASSESSMENT GUIDE - After reading the two short PDFs above, then go to the appropriate Socrative room and complete the series of multiple choice and free response questions.   This assignment will share how to build your personal brand and how to promote it on LinkedIn. 

2nd Period go to Socrative Room   GHCDF2

3rd Period go to Socrative Room   GHCDF3

4th Period go to Socrative Room   GHCDF4

Well that’s it for now.  Contact me with any questions or comments.  Good luck with the start of your week and be safe, Mr. Nelson

**************************************************************************************************************************

Week #2 (3/23-27/2020) - Remote Learning Assignments

This week, you’ll complete another KM Hotel lesson ( “Marketing & Public Relations” ), but for variety I have integrated a unit on LinkedIn profiles.  This unit will expose you to this important communication tool and will advance your college and career preparedness. 

Complete Knowledge Matters Lesson “Marketing & Public Relations” 

Due Friday,  March 27  5:00pm 

Complete LinkedIn Lesson #1 Introduction to LinkedIn 

Due Wednesday, March 25  5:00pm 

Step #1 Read  LinkedIn Profile Checklist for High School Students    

Contact Mr. Nelson if you encounter any download issues.

Step #2 Go the Socrative Room for your period and complete the posted REVIEW & SELF ASSESSMENT GUIDE 

After reading LinkedIn Profile Checklist for High School  S tudents , go to the appropriate Socrative room and complete the series of multiple choice and free response questions.  This assignment will guide you through the basic layout of a LinkedIn profile, and will begin to guide you through the development of your own profile. 

COMING ATRACTIONS

LinkedIn Lesson #2 Starting Your LinkedIn Profile  (Future Date TBD)

LinkedIn Tip Sheets

LinkedIn Tip Sheet - Building A Great Student Profile

SOCRATIVE SELF ASSESSMENT GUIDE - After reading the two short PDFs above, then go to the appropriate Socrative room and complete the series of multiple choice and free response questions.   This assignment will be due Friday April 3.

LinkedIn Lesson #3 Refining Your LinkedIn Profile (Future Date TBD)

Future LinkedIn Reading Assignments

More LinkedIn Tip Sheets

LinkedIn Lesson #4 From Prolie to College Application (Future Date TBD)

Other On-line Resources

Use LinkedIn To Get Into Your Dream College

******************************************************************************************************************************************************************

REMOTE INSTRUCTION ASSIGMENT HISTORY 

Week #1 (3/16-20/2020) - Remote Learning Assignments

This week, we will complete the first two lessons in the Knowledge Matters (KM) Hotel simulation.  For those absent on Friday (March 13), please add the following course code to your Knowledge Matters accounts.

Period Two -  JE6CS7

Period Three -  NE7TE8

Period Four -  GL7NZ3

Each lesson will require you to complete a reading quiz, math quiz and simulation training (same as past KM simulation units) .  Minimum scores for the reading quiz have been set to 70% for the reading quiz and 60% for the simulation training (automatic retake if you get less).  You will take the math quiz but this score will not influence your weekly grade.  We will revisit some of these math topics in future week(s) of remote instruction. 

Here’s the first two lessons to complete this week.  These assignments will be due at midnight on Friday March 20, 2020.  

Lesson #1 - Pricing & Revenue Management

Lesson #2 - Group Sales

ASSESSMENT NOTES: For continuity, the GHC administration has asked teachers to post one and only one grade for each week of remote instruction.  The weekly grade will be posted a couple days after the due date.  My plan is to segregate the weekly grades for remote learning weeks and weighting them proportionately with the number of weeks that school is shut down.  This approach will likely benefit most students’ grades.  I reserve the option of modifying these grade guidelines for accuracy and fairness.  Know that my overarching philosophy is to give students the benefit of the doubt in light of these unprecedented events.  

PRE-REMOTE INSTRUCTION LINKS - FOR NOW, IGNORE EVERYTHING BELOW THIS POINT

For Ideas - Look at Mr. Nelson’s Past Recommendation Excerpts 

Virtual Business Challenge Round One Results

Virtual Business Challenge Round Two Results

5 Reasons High School Students Should Use LinkedIn

LinkedIn To College Free E-Book

Quant Crunch

Section #1 Financial Functions    Day of Final/Seniors Wednesday

One Function Questions, NPV & IRR

Practice Financial Functions Practice Test #A3

Practice Financial Functions Test #A3 Annotated Answers

Practice Financial Functions Test #A3 Answers PDF Format

Practice Financial Functions Practice Test #A4

Practice Financial Functions Test #A4 Annotated Answers

Practice Financial Functions Test #A4 Answers PDF Format

Practice Financial Functions Practice Test #A5

Practice Financial Functions Test #A5 Annotated Answers

Practice Financial Functions Test #A5 Answers PDF Format

Practice Financial Functions Practice Test #A6

Practice Financial Functions Test #A6 Annotated Answers

Practice Financial Functions Test #A6 Answers PDF Format

Practice Financial Functions Practice Test #A7

Practice Financial Functions Test #A7 Annotated Answers

Practice Financial Functions Test #A7 Answers PDF Format

Composite Financial Functions

Financial Functions #1

Financial Functions #2

Financial Functions #1 & #2 Excel

Financial Functions Annotated Answers #1  

Financial Functions Annotated Answers #2

Financial Functions #3      

Financial Functions Annotated Answers #3 (Excel)   

Financial Functions Annotated Answers #3 (PDF)  

Section #2 Mathematical Modeling:  Final May 10

Spring Final Practice

Excel File Showing Work From Class Example

Linear         Exponential         Logarithmic       Quadratic      Power

Auto Sales Data

Blank Mathematical Modeling Answer Form

CLASSWORK Excel File from January 25 & 26

Mathematical Modeling Practice January 29 & 30

Practice Tests #1A, #1B, #2A, #2B  

Section #3 Normal  Probability Distributions:  Population & Sampling

Final May 10

Normal Probability Practice Test

Normal Probability Test Annotated Answers (Excel)  

Normal Probability Test Annotated Answers (PDF)

Practice Test - Tuesday/Wednesday Class

Normal Probability Calculations As Reviewed In Class

Section #4 Excel Vocabulary  Day of Final/Seniors Wednesday

Best Way to Study: Go to Socrative Room #GHCDH 1

CHASE's QUIZLET Lessons 1-3 & 5

HANNAH's QUIZLET Lessons 4-8

Section #5: Inference Procedures  

Classwork Questions  - Assigned  Monday April 8 - Due Tuesday Period 1 & Due Wednesday Period 2

DATA For Confidence Intervals

Inference Forms  (Scaffolds 4-step Process)

Confidence Interval - Mean

Confidence Interval - Proportion

Test of Significance - Mean

Test of Significance - Proportion

Chai Square Test

Inference Practice Problems

A1 & B1 Excel Answer         A1 PDF       A1 Graph PDF     B1 PDF      B1 Graph PDF

C1 Excel Answer            C1  PDF            C1 Graph PDF

A2 Excel Answer          A2 PDF

B2 Excel Answer          B2 PDF

C2 Excel Answer          C2 PDF

  A3 Excel Answer            A3 PDF

B3 Excel Answer            B 3 PDF

C3 Excel Answer        C3 PDF

A4 Excel Answer           A4 PDF        A4 Graph PDF

B4 Excel Answer            B4 PDF       B4 Graph PDF

C4 Excel Answer            C4  PDF       C4 Graph PDF

Section #6:   Career Readings - Soft Skills Demand

Reading Quizzes Practice - Socrative Room GHCDF1 

(Thank you to Burning Glass Technologies)

The Digital Edge

The Quant Crunch

Human Factor Baseline Skills

Section #7:    Survey & Experiment Vocabulary & Design 

Study Vocabulary In Socrative Room #GHCDF1 (No supports)

Study Reading Quiz Questions Room #GHCDH1 (Open reading selection format)

Section #8:    Discrete Bivariate Probability   Final May 10

Board Answers For Two Practice Tests Completed In Class

Section #9:    Univariate Data Analysis      FINAL Wednesday, May 21  

Univariate Graphic Display Practice Problems  

Study the materials above in addition to performing basic data analysis using Excel Toolpak.

Practice Test GHCDH3

Section #10:    Bivariate Data Analysis   FINAL Wednesday, May 21

#1  Practice Midterm Excel Spreadsheet

#1   Practice Bivariate Midterm PDF              Answers Practice Bivariate Midterm PDF

#2  Practice Midterm Excel Spreadsheet

#2   Practice Bivariate Midterm PDF                                Answers Practice Bivariate Midterm PDF

BDA Class Practice Monday & Tuesday

Section #11:    Expected Value & Probability Rules    Day of Final/Seniors Wednesday

(Note: Normal  Probability Has Already Been Assessed)

#1  Basic Probability Rules, Normal Curves, & Expected Value (Stock )

#1  Answers for Basic Probability, Normal & EV (Excel File)

#1  Answers for Basic Probability, Normal & EV (PDF File)

#2  Basic Probability Rules, Normal Curves, & Expected Value (Stock)

#2  Answers for Basic Probability, Normal & EV (Excel File)

#2  Answers for Basic Probability, Normal & EV (PDF File)

DON'T WORRY ABOUT STUFF BELOW THIS LINE!!!!!!!

Section #5 Statistical Symbols    

Practice Symbols Test

LinkedIn Lessons

LINKEDIN  INTRODUCTION: WHY HAVE A PROFILE?

“Sharespark Media - published on Utube May 2016 - 5:18 in length"

LinkedIn Profile Checklist  (Good Overview For High School Students)

Build Your Personal Brand on LinkedIn

LinkedIn For Students

LinkedIn Building A Great Student Profile

Pensions: Defined Benefit Vs. Defined Contribution

Pensions: Underfunded State Obligations

Chart Comparing Defined Benefit & Defined Contribution

TYRA BANKS FINAL DATA - Use This File For Histograms & Two-Sample Tests of Significance

PRACTICE Financial Functions EXAMS #A, #B, #C, #D

Excel Answer Calculations

ONLINE DATA ROBERT SHILLER

RAW DATA From Video Example of Pivot Tables

Spring Midterm #1 

Section #1 Composite Financial Functions

Section #2 Mathematical Modeling: 

Section #4 Normal  Probability Distributions:  Population & Sampling

Section #5 EXCEL Vocabulary

Definitions will match those provided in the hand-outs.  Review all key terms for all lessons.  Here's the lists.

Key Terms:           Lesson One           Lesson Two           Lesson Three        Lesson Four     

         Lesson Five                  Lesson Six           Lesson Seven           Lesson Eight    

Sampling Surveys

Observational Study Design Glossary Assignment

Students will create a custom glossary by copying the definitions of terms from the two links below.  The list of terms to be included in the Glossary are provided in the first posted document below.  Understanding these terms will be critical when students soon begin designing their own sampling surveys.  These terms and symbol notations will comprise the majority of the vocabulary section of the first spring midterm.  ALL GLOSSARIES MUST BE  HANDWRITTEN , & TERMS  NUMBERED AS SHOWN  .  THE GLOSSARY SHOULD BE  ORGANIZED IN OUTLINE FORM  AS SHOWN IN THE "LIST OF TERMS".  

Stat Trek Survey Sampling   Source: stattrek.c0m

Additional Survey Terms    Source: sciencebuddies.org

Khan Academy Video: Sampling Methods & Forms of Bias  

SCDC 2018 - Time To Dominate

ICDC Finance 2013-2016

ICDC Principles 2013-2016

ASSIGNMENT #2: DUE   TBD

Survey Design Tutorial

Students submit notes from reading assignment, "Designing Surveys & Questionairres".  Here's the sections you  DO NOT  have to read.

"Pre-Notification Letters", "Notification of Cut-off Date", "Reply Envelopes and Postage", "The Outgoing Envelope and Postage", "The Meaning of Significance" 

How to Analyze Apartment Building Financials

11922 Runnymede Street, North Hollywood

5252 Cahuenga Blvd., North Hollyood

1819 S. Gramercy Place, Los Angeles

Apartment Finder

Great Depression vs. 'Great Recession'

Great Depression Versus Great Recession Powerpoint

Is today's economic crisis another Great Depression?   

Wordle Of Article               USA Today November 2008

Economy: Depressing but not a Great Depression

Tent Cities Spring Up in LA

Practice #A

Practice #B

Practice #C

Note: Answer to Practice Test B #8 NPV = $1,281,392  (Use 9%, not 8%)

Here's more instructional materials for your review of financial functions.  This practice was provided earlier in the semester. 

Practice Problems ANSWERS For Tests #1 & #2 EXCEL File                       

Practice Test #1 ANSWERS PDF File

Practice Test #2 ANSWERS PDF Fil

HERE’S THE FIRST STEP TO FINISHING BUSINESS STATISTICS

FALL 2018 FINANCIAL FUNCTIONS

(Don't be concerned about the difference in the title above the annotated answers.)  

Spend Three Hours on Hotel Mogul Simulation 

Due Friday, May 15  11:59pm (midnight)

• How it works

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Coding boot camp BloomTech and CEO Austen Allred deceived students, US government agency says

• The CFPB issued an order against coding boot camp BloomTech and CEO Austen Allred.
• The CFPB said BloomTech, formerly known as Lambda School, deceived students.
• BI previously reported allegations that BloomTech misled students about job placement rates and education quality.

The Consumer Financial Protection Bureau issued an order against coding boot camp BloomTech and its CEO, Austen Allred , on Wednesday.

The CFPB said the coding boot camp, previously known as Lambda School, deceived students about the cost of loans and made false claims about graduates' hiring rates.

The government agency banned Allred from student-lending activities for 10 years and permanently banned BloomTech from all consumer-lending activities. In addition, BloomTech must pay $64,000 and Allred must pay $100,000 in civil penalties, which will go toward a victim relief fund, according to the agency .

The crackdown follows exclusive reporting by Business Insider about the activities of BloomTech and allegations against the company.

BloomTech was founded in 2017 as Lambda School . At the time, it was considered a pioneer in the income share agreement (ISA) model, meaning that students didn't have to pay tuition upfront to attend the boot camp. Instead, they would pay a share of their income each month to the school after landing a job paying above a certain amount.

The CFPB said BloomTech falsely told students that the ISAs were not loans, when the loans carried an average finance charge of $4,000. The agency also noted that a single missed payment could trigger a default, leading to the remainder of tuition being due immediately. It said BloomTech did not disclose key terms like the finance charge and annual percentage rate, as required by law.

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It also found that BloomTech inflated its job placement rate, saying 71% to 86% of its graduates landed jobs, while internal metrics shown to investors were closer to 50%.

A sample size of one

At one point, Allred tweeted that the school achieved a 100% job-placement rate in one of its cohorts, and later acknowledged in a private message that the sample size was just one student, the CFPB said.

Leaked documents showed that BloomTech's job placement rate in qualifying jobs during the first half of 2020 was only around 30%, Business Insider previously reported.

The CFPB ordered BloomTech and Allred to stop collecting payments on ISA loans for graduates who didn't have a qualifying job. Its ISA loan terms must eliminate the finance charge for students who graduated the program more than 18 months ago and obtained a qualifying job making $70,000 or less. The school also must allow students the option to withdraw from the program without penalty.

"BloomTech and its CEO sought to drive students toward income share loans that were marketed as risk-free, but in fact carried significant finance charges and many of the same risks as other credit products," CFPB Director Rohit Chopra said.

Allred wrote in a post on X that BloomTech " decided to settle the matter because it was clear that ongoing litigation would be extremely time consuming, incredibly expensive, and distract us from our core mission. We do so without agreeing to or denying any of the allegations in the consent order."

"BloomTech continues to focus on its core mission: improving the lives of students and enabling them to fulfill their economic potential," he added. "While it's been frustrating, we're glad to put this behind us."

Several students previously took legal action against BloomTech, alleging it misrepresented its job placement rate, BI reported.

BI also previously reported on student complaints about the quality of education and lack of assistance in landing tech jobs. At the time, the coding boot camp faced a fine from a California agency for violating state law by failing to register itself properly.

Got a tip? Contact this reporter via email at [email protected] , Signal at 646.376.6106, or Telegram at @rosaliechan. (PR pitches by email only, please.) Other types of secure messaging available upon request.

Watch: Nearly 50,000 tech workers have been laid off — but there's a hack to avoid layoffs

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• Authors: Alexander Holmes, Barbara Illowsky, Susan Dean
• Publisher/website: OpenStax
• Book title: Introductory Business Statistics
• Publication date: Nov 29, 2017
• Location: Houston, Texas
• Book URL: https://openstax.org/books/introductory-business-statistics/pages/1-introduction
• Section URL: https://openstax.org/books/introductory-business-statistics/pages/1-key-terms

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