Statistics Applied to Managerial Problems

Statistics Applied to Managerial Problems

 

 

MBA Program Outcomes: 1. Synthesize concepts from various business disciplines to develop business strategies. 2. Develop a leadership framework to evaluate ethical issues in business. 3. Anal

 

As a student of Concordia University Chicago and a member of the larger society, I pledge to uphold an academic honor code that supports serving and leading with strong personal integrity. Specifically, this included not cheating or using inappropriate or dishonest means in the completion of academic requirements. This also includes not giving unauthorized assistance to others. I understand that it is my responsibility to comply with this honor system.

 

This honor code is available for review on the Concordia University website. As a result of your commitment to this honor code, violations of the code will have serious repercussions. Academic consequences resulting from violations of the Honor Code could range from a zero on the assignment or examination (which will count in your overall point total for this course) to failure of the course. Multiple violations will be reviewed by the Honor Code Council and could result in a failing course grade, suspension or expulsion from the university.

 

Concordia Honor Code

 

In accordance with the honor code that you have signed, turning in any piece of work, which includes your digital signature, constitutes your pledge that your documents are original and that you have not given or received any unauthorized assistance in completing your assignments.

 

Plagiarism Plagiarism is defined as use of intellectual material produced by another person without acknowledging its source. CUC faculty members monitor student work.

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For example: • Widespread copying of passages from works of others into an assignment, paper, discussion board posting, or thesis or dissertation without acknowledgment. • Using the views, opinions, or insights of another without acknowledgment. • Paraphrasing another person’s characteristic or original phraseology, metaphor, or other literary device without acknowledgment.

 

Accommodations Statement Concordia University and the faculty will make all reasonable efforts to accommodate any student with a documented learning, physical or mental impairment in the teaching or evaluation of students. All specific needs must be on record with Concordia University’s Center of Accommodations and Resource for Excellence (CARE).  Students with disabilities should contact CARE, located on the lower level of the Klinck Memorial Library, for information concerning accommodations in the classroom. A diagnosis and documentation of testing by a licensed professional must be submitted to CARE before services may be received.

 

For further information or to request an accommodation, please contact: Dirvelys J. Allen Academic Support Coordinator 708-488-4109 Dirvelys.Allen@Cuchicago.edu

 

Class Attendance and Participation Policy: Research clearly indicates that class attendance is an integral factor in student learning.  The importance of attendance is even more amplified in the Concordia eight-week term.  Any student who is absent 25% or more of the designated instructional time may receive a grade of “F” for the course. Your online course room attendance is required and it is highly suggested that you maintain a minimum online course room presence of at least 3 days a week, with no more than 2 consecutive days without being present in the university’s course room environment; this requirement may seem less stringent than in other courses, but that is due to the nature of the subject requiring you to do  more self-directed learning and practicing a quantitative skill, and so students may move at different paces each week.  If you encounter an unexpected circumstance that results in an extended absence, you are required to communicate with your instructor and your academic advisor to request an official leave of absence. Emergency situations will be considered on a student-by-student basis.

 

Students are responsible for participating in this course through the following academic activities: • completing assigned readings from texts / ebooks, websites and supplemental articles, • watching uploaded video lectures and links to online videos, • responding to module discussion questions by posting to discussion boards on time, • participating in the discussions with classmates and instructor, • participating in the weekly activities and posting as required, • completing the weekly conceptual quizzes by the due date, • completing the practice problems (as needed) in preparation for the graded assignment, and • submitting assignments for each learning module by the due date.

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This course is organized by weekly learning modules. All assigned readings and video lessons for the module are to be completed before completing assignments; attempting to do the assignments first will likely result in poor performance and / or frustration.  After completing the assigned readings and videos, students may choose (in any order) to complete the quiz, respond to the posted discussion questions, and participate in the weekly activity.  Students should also complete practice problems as needed before attempting the assigned problems which are to be submitted for a grade. Instructions for responding to the Discussion Questions are provided.

 

Late Policy: Given the nature of this course building on itself, assignments must be completed before moving on to the next unit. Thus, late assignments will only be tolerated for a short period to keep students on track; there will be a grade penalty of 1/2 point per day late (out of the 4 point maximum) unless the lateness is due to documented serious illness or family emergency.  Assignments over 5 days late will not be accepted.  Exceptions to this policy will be made on a case-by-case basis at the instructor’s discretion.

 

Posting and Responding to Discussion Questions: Discussions require a response to specific questions that results in collaborative conversations and construction of knowledge that builds and expands learning within the course. As a master’s level student, it is expected that you will reply as a practitioner-scholar.

 

You must support your Discussion postings and responses with academically appropriate references, unless you are asked to provide personal opinion or personal reflection for a specific question. Unless noted otherwise, your initial discussion postings should be approximately 250-300 words in length, substantive and scholarly in nature. Please refer to the College of Business power point “Engaging in Dialogue.” You are required to respond to each Discussion posting, each week, within each module and provide a minimum of two responses (100-150) to colleagues in the following ways:

 

• Suggest why you might see things differently. • Ask a probing or clarifying question. • Share an insight from having read the colleague’s posting. • Offer and support an opinion. • Validate an idea with your own experience. • Make a suggestion. • Expand on the colleague’s posting. • Ask for evidence that supports the posting. • Always be respectful and collegial. • Craft grammatically correct responses.

 

Discussion Reflection: At the end of each week, you are required to post your substantive reflection based on your readings and peer engagement.

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CONCORDIA UNIVERSITY CHICAGO COLLGE OF BUSINESS MASTER OF BUSINESS ADMINISTRATION (MBA) Online Syllabus

 

Technology Expectations: A. Students will complete assignments using Microsoft Excel; students may opt to use other statistical software, but it will be at their own risk, and the instructor is not expected to answer questions regarding that software. B. Students will be using internet search engines for some discussions and activities. the Internet and library-technology based database, such as the university’s research database when conducting literature searches and course assignments and discussions. C. Students will interact with their instructor and other classmates through the Blackboard virtual classroom, including: retrieving their syllabus, participating in structured discussions and activities, submitting assignments, and communicating with their professor. D. Students are expected to use their Concordia email for all correspondence. Students should log into Concordia Connect to check their email on a regular basis.

 

Request for an Incomplete: Please be aware that incomplete grades are generally not granted, although an expectation may be allowed for verifiable circumstances. At least 75-80 percent of course work should be completed in order for an incomplete request to be considered. If you are granted an incomplete, according to University policy, you have 6 weeks to submit the remainder of your syllabus requirements and receive a final grade assessment.

 

Course Description

 

MBAC 6400 Statistics Applied to Managerial Problems

This course provides students with an understanding of statistical data for the primary purpose of managerial problem solving and decision making.  Topics include probability distributions, estimation and hypothesis testing, quality control and regression analysis. Applications of statistical techniques to issues in marketing, investment analysis and manufacturing are discussed.

 

COURSE LEARNING OUTCOMES This course should enable the student to:

 

1. Develop an understanding of ethics and social responsibility as applied to conducting research and reporting analysis results. 2. Sharpen and apply critical thinking skills in the design of statistical methodology, the analysis of data and the interpretation of results. 3. Practice written communication in discussing statistical concepts and in presenting results and conclusions of the statistical analysis of real data. 4. Embrace diversity and promote inclusivity through discussion and collaboration with students across the world as well as the application of statistical analysis to real world data.

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CONCORDIA UNIVERSITY CHICAGO COLLGE OF BUSINESS MASTER OF BUSINESS ADMINISTRATION (MBA) Online Syllabus

 

PRINCIPAL UNITS TAUGHT IN THE COURSE:

 

1. Descriptive statistics (which includes using graphs, tables and words to describe data) and sampling (which includes the methodology for getting representative data ethically). B. Probability and probability distributions, which includes computing probability for discrete data, computing probability for continuous data using the normal probability distribution and computing confidence intervals needed for inferential statistics. C. Hypothesis testing of one, two or multiple samples to analyze means, proportions or categorical data to determine if significant differences or relationships exist. D. The application of all topics covered in the course as students analyze a data set and write up their findings in a comprehensive course project.

 

Diversity Students are expected to respect diversity of thought, opinion, and background in all aspects of interaction and communication. The course incorporates and supports aspects of a diverse learning society.

 

Required Text An online textbook along with supplementary links will be provided. Students may choose to purchase additional materials as needed to help with understanding and practicing statistics.

 

Research Please check the course room for suggested links to pertinent and timely websites or articles.

 

Course Activity Outcome Activity Name Description/Due in Module # Course Outcome Assessed Point value/ Percentage

#1 #2 #3 #4

Participation 1-7 (includes weekly discussions and activities)

 

Due in modules 1 – 7

√  √ √

3 pts @= 21pts

Quizzes 1 – 7 (highest score counts each week) Due in modules 1 – 7

√ √   3 pts @= 21pts

Assignments 1 – 7 Due in modules 1 – 7

√ √ √ √

4 pts @= 28pts.

Reflection Paper Module 8

√ √ √ √

5 pts.

Portfolio Assignment Module 8

√ √ √ √

25 pts. Total      100 pts.

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• The Participation grade will be a score of 0, 1, 2 or 3 based on the degree to which the student has met all posting requirements. A 3 indicates an excellent job with minimal omissions; a 2 indicates good work with some area for improvement; a 1 indicates partial participation or excessive areas for improvement; a 0 indicates little to no participation or submissions beneath graduate standards. Instructors may choose to award half points (e.g., 2.5 out of 3) at their discretion. • The Quiz grade will be computed automatically, with each question having a designated point value and the total being 3 points (e.g., there may be 12 questions worth 1/4 point each). Students may attempt the quiz unlimited times until the due date, after which the highest score counts officially. • The Assignment grade will be a score of 0, 1, 2, 3 or 4 based on completeness and accuracy. The scoring will follow the grade point system, with a 4 indicating “A” level work, a 3 indicating “B” level work, a 2 indicating “C” level work, a 1 indicating “D” level work, and a 0 indicating “F” level work. Instructors may choose to award half points (e.g., 2.5 out of 4) at their discretion. Late penalties will be 1/2 point per day, with an automatic 0 after 5 days (unless an exception is made). • There will be a maximum of 10 points awarded for each of the first 7 modules, with the portfolio worth the remaining 30 points. A rubric for the portfolio grading will be provided.

 

 

Grading Scale 100-93% A 4.00 82-80% B- 2.67 69-67% D+ 1.33 92-90% A- 3.67 79-77% C+ 2.33 66-63% D 1.00 89-87% B+ 3.33 76-73% C 2.00 62-60% D- .67 86-83% B 3.00 72-70% C- 1.67 59% & below F .00

 

 

 

Quick Reference to Module Activities Start Date Weeks Topics and Module Readings/ Resources Assignments and Activities Monday of Week 1 Week 1 Module 1 • Course Introduction • Discussion 1 • Activity 1 • Quiz 1 • Assignment 1 • Review Syllabus • Read unit 1 of lecture notes (ebook) and other materials as directed • Watch unit 1 video lecture and other videos as directed • Discussion Forum #1 Your Post-Due Thursday by 11:59pm Reply to Peers’ (1 minimum per question) & Reflection post -Sunday by 11:59pm. • Activity #1 Your Post-Due Friday by 11:59pm • Quiz #1 Multiple attempts permitted until Sunday at 11:59 pm (highest score counts) • Assignment  #1 Due Sunday at 11:59 pm

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Monday of Week 2

Week 2 Module 2 • Discussion 2 • Activity 2 • Quiz 2 • Assignment 2

• Read unit 2 of lecture notes (ebook) and other materials as directed • Watch unit 2 video lecture and other videos as directed
• Discussion Forum #2 Your Post-Due Thursday by 11:59pm Reply to Peers’ (1 minimum per question) & Reflection post -Sunday by 11:59pm. • Activity #2 Your Post-Due Friday by 11:59pm • Quiz #2 Multiple attempts permitted until Sunday at 11:59 pm (highest score counts) • Assignment #2 Due Sunday at 11:59 pm

Monday of Week 3

Week 3 Module 3 • Discussion 3 • Activity 3 • Quiz 3 • Assignment 3

• Read unit 3 of lecture notes (ebook) and other materials as directed • Watch unit 3 video lecture and other videos as directed
• Discussion Forum #3 Your Post-Due Thursday by 11:59pm Reply to Peers’ (1 minimum per question) & Reflection post -Sunday by 11:59pm. • Activity #3 Your Post-Due Friday by 11:59pm • Quiz #3 Multiple attempts permitted until Sunday at 11:59 pm (highest score counts) • Assignment #3 Due Sunday at 11:59 pm

Monday of Week 4

Week 4 Module 4 • Discussion 4 • Activity 4 • Quiz 4 • Assignment 4

• Read unit 4 of lecture notes (ebook) and other materials as directed • Watch unit 4 video lecture and other videos as directed
• Discussion Forum #4 Your Post-Due Thursday by 11:59pm Reply to Peers’ (1 minimum per question) & Reflection post -Sunday by 11:59pm. • Activity #4 Your Post-Due Friday by 11:59pm • Quiz #4 Multiple attempts permitted until Sunday at 11:59 pm (highest score counts) • Assignment #4 Due Sunday at 11:59 pm

Monday of Week 5

Week 5 Module 5 • Discussion 5 • Activity 5 • Quiz 5 • Assignment 5

• Read unit 5 of lecture notes (ebook) and other materials as directed • Watch unit 5 video lecture and other videos as directed
• Discussion Forum #5 Your Post-Due Thursday by 11:59pm Reply to Peers’ (1 minimum per question) & Reflection post -Sunday by 11:59pm. • Activity #5 Your Post-Due Friday by 11:59pm • Quiz #5 Multiple attempts permitted until Sunday at 11:59 pm (highest score counts) • Assignment #5 Due Sunday at 11:59 pm

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CONCORDIA UNIVERSITY CHICAGO COLLGE OF BUSINESS MASTER OF BUSINESS ADMINISTRATION (MBA) Online Syllabus

 

Monday of Week 6

Week 6 Module 6 • Discussion 6 • Activity 6 • Quiz 6 • Assignment 6

• Read unit 6 of lecture notes (ebook) and other materials as directed • Watch unit 6 video lecture and other videos as directed
• Discussion Forum #6 Your Post-Due Thursday by 11:59pm Reply to Peers’ (1 minimum per question) & Reflection post – Sunday by 11:59pm. • Activity #6 Your Post-Due Friday by 11:59pm • Quiz #6 Multiple attempts permitted until Sunday at 11:59 pm (highest score counts) • Assignment #6 Due Sunday at 11:59 pm

Monday of Week 7

Week 7 Module 7 • Discussion 7 • Activity 7 • Quiz 7 • Assignment 7

• Read unit 7 of lecture notes (ebook) and other materials as directed • Watch unit 7 video lecture and other videos as directed
• Discussion Forum #7 Your Post-Due Thursday by 11:59pm Reply to Peers’ (1 minimum per question) & Reflection post – Sunday by 11:59pm. • Activity #7 Your Post-Due Friday by 11:59pm • Quiz #7 Multiple attempts permitted until Sunday at 11:59 pm (highest score counts) • Assignment #7 Due Sunday at 11:59 pm

Monday of Week 8

Week 8 Module 8 • Portfolio Assignment

• Portfolio Assignment Due Sunday at 11:59 pm

 

Assignments

Assignment #1: Graphing & Descriptive Statistics – 4 pts.  Due at the end of Module 1.

Practice Problems:  Student data (Do not submit) Use the Student.xls file which consists of 100 fictional graduate students at Concordia.  It includes variables regarding their age, gender, major, employment status, BS GPA, MBA GPA, and weekly hours spent studying. • PRACTICE PROBLEM 1:  Using the CATEGORICAL_ANALYSIS.xls file, perform a categorical analysis on the majors of students enrolled in the MBA.  Describe your findings. • PRACTICE PROBLEM 2:  Using the FREQUENCY_DISTRIBUTION.xls file, create a frequency distribution & histogram on the GPAs of the students.  Use ranges of 2.50-2.75, 2.75- 3.00, 3.25-3.50, 3.50-3.75 and 3.75-4.00.  Describe your findings. • PRACTICE PROBLEM 3:  Using the DESCRIPTIVE_STATISTICS.xls file, compute the descriptive statistics for the weekly hours spent studying.  Describe your findings. Solutions are provided to practice problems so you can check your work.

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Assigned Problems: Mutual Fund data (Submit by the end of Module 1) Use Mutual_Funds.xls file which consists of 194 different mutual funds from various companies.  It includes variables regarding the name, the net asset value (NAV), the 1-year return, the types of fees, the fund objective, and the size of the fund. • ASSIGNED PROBLEM 1: Using the CATEGORICAL_ANALYSIS.xls file, perform a categorical analysis on fees for the mutual funds.  Describe your findings. • ASSIGNED PROBLEM 2: Using the FREQUENCY_DISTRIBUTION.xls file, create a frequency distribution & histogram on the NAVs.  Use ranges of 0 – 10, 10 – 20, 20 – 30, 30 – 40, 40 – 50, 50 – 60, 60 – 70 and 70 – 80.  Describe your findings. • ASSIGNED PROBLEM 3: Using the DESCRIPTIVE_STATISTICS.xls file, compute the descriptive statistics for the 1-year return of the mutual funds. Describe your findings.

 

Expectations:  Copy & paste the Excel displays into a Word file if you can. Upload the Word file (or the Excel files) for credit.  Comments in which you describe your findings should be included with each display.  APA formatting is not required for weekly assignments but adhere to the rules of written English in your punctuation, grammar and spelling.

 

Course Learning Outcomes: 1, 2, 3 & 4

 

Assignment #2: Probability & the Normal Distribution – 4 pts.  Due at the end of Module 2.

Practice Problems:  Student data (Do not submit) Use the Student.xls file for the following problems: • PRACTICE PROBLEM 1: Create a pivot table of Gender and Major. Then using the JOINT_PROBABILITY.xls file, complete the Joint Probability table so you can answer the following: a) What is the probability of randomly choosing a Female? b) What is the probability of randomly choosing a Male AND Finance major? c) What is the probability of randomly choosing a Female OR Leadership major? d) Given that the home you selected is a Male, what is the probability he has no major? e) Given that the home you selected has no major, what is the probability the student is male? • PRACTICE PROBLEM 2: Let’s assume that the Student_Data.xls file was the entire population. We know the mean and standard deviation of student ages to be 42.3 and 8.9, respectively. Using the NORMAL_PROBABILITY.xls file, compute the percentage of students that are older than 50, younger than 40, between 41 and 46, and oldest 10% are at what age? Then compare to the truth as found in the actual file. Solutions are provided to practice problems so you can check your work.

 

 

Assigned Problems:  Low Birth Weight data (Submit by the end of Module 2) Use Low_Birth_Weight.xls file which consists of data from 189 births.  It includes variables regarding the birth weight of the baby, whether it was low weight, the age of the mother, the weight of the mother, the race of the mother, whether the mother smoked, whether the labor was premature, whether the mother had a history of hypertension, and whether the mother had uterine irritability.

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CONCORDIA UNIVERSITY CHICAGO COLLGE OF BUSINESS MASTER OF BUSINESS ADMINISTRATION (MBA) Online Syllabus

 

• ASSIGNED PROBLEM 1: Create a pivot table of Race and Low Birth Weight. Then using the JOINT_PROBABILITY.xls file, complete the Joint Probability table so you can answer the following: a) What is the probability of randomly choosing a Black woman? b) What is the probability of randomly choosing a White woman AND a Low birth weight? c) What is the probability of randomly choosing a Black woman OR a Low birth weight? d) Given that the mother you selected is a White, what is the probability she had Low birth weight? e) Given that the mother had Low birth weight, what is the probability she is Black? • ASSIGNED PROBLEM 2: Let’s assume that the Low_Birth_Weight.xls file is a random sample from the Concordia Hospital in 2015. The mean birth weight is approximately 6.5 pounds with a standard deviation of 1.6 pounds. The national standard is that a birth weight below 5.5 pounds is considered to be low. Using the NORMAL_PROBABILITY.xls file, compute the following: a) What is the probability of a low birth weight (< 5.5 pounds) occurring at Concordia? b) What is the probability of a birth weight being above the national average of 7.5 pounds? c) What is the probability of a birth weight being between 5 and 6 pounds? d) The bottom 10% of births by weight are below what weight?

 

Expectations:  Copy & paste the Excel displays into a Word file if you can. Upload the Word file (or the Excel files) for credit.  Comments in which you describe your findings should be included with each display.  APA formatting is not required for weekly assignments but adhere to the rules of written English in your punctuation, grammar and spelling.

 

Course Learning Outcomes: 1, 2, 3 & 4

 

Assignment #3: Confidence Intervals & Sample Sizes – 4 pts. Due at the end of Module 3. Practice Problems:  Student data (Do not submit) Use the Student.xls file for the following problems: • PRACTICE PROBLEM 1: You wish to know the average GPA of MBA students at Concordia. Compute the 95% confidence interval of the mean using the sample of 200 students. Describe your findings. • PRACTICE PROBLEM 2: You wish to know the proportion of MBA students that are majoring in Finance.  Compute the 95% confidence interval of the proportion using the sample of 200 students.  Describe your findings. • PRACTICE PROBLEM 3: You wish to learn the average age of an MBA student within 2 years and with 99% confidence. How large of a sample should you get? (Note:  the standard deviation of the student ages is 8.93). • PRACTICE PROBLEM 4: You wish to learn the proportion of MBA students that are female within 3%, and with 98% confidence. How large of a sample should you get? Solutions are provided to practice problems so you can check your work.

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CONCORDIA UNIVERSITY CHICAGO COLLGE OF BUSINESS MASTER OF BUSINESS ADMINISTRATION (MBA) Online Syllabus

 

Assigned Problems:  Garbage data (Submit by the end of Module 3) Use Garbage.xls file which consists of data from 60 fictional homes on Concordia St.  It includes variables regarding the household size, the pounds of each type of garbage disposed in a week, the total weight of their garbage each week, and whether or not the household recycles. • ASSIGNED PROBLEM 1: First compute the mean total weight and standard deviation of the garbage disposed each week by the sample; use the Descriptive_Statistics.xls file if needed. Then compute the 95% confidence interval of the mean total garbage disposed of in a week on Concordia St.  Describe your findings. • ASSIGNED PROBLEM 2: First compute the proportion of homes in the sample that recycle. Then compute the 95% confidence interval of the proportion of homes on Concordia St. that recycle. Describe your findings. • ASSIGNED PROBLEM 3: You wish to learn the average number of pounds of garbage disposed of in a week by the people on Concordia St. within 2 pounds. Using the standard deviation from problem 1as an estimate, how large of a sample should you get? • ASSIGNED PROBLEM 4: You wish to learn the proportion of homes on Concordia St. that recycle within 10% and with 99% confidence.  How large of a sample should you get?

 

Expectations:  Copy & paste the Excel displays into a Word file if you can. Upload the Word file (or the Excel files) for credit.  Comments in which you describe your findings should be included with each display.  APA formatting is not required for weekly assignments but adhere to the rules of written English in your punctuation, grammar and spelling.

 

Course Learning Outcomes: 1, 2, 3 & 4

 

Assignment #4: One Sample Hypothesis Testing – 4 pts. Due at the end of Module 4. Practice Problems:  Student data (Do not submit) Use the Student.xls file for the following problems: • PRACTICE PROBLEM 1:  It is pretty common across most schools to find the grades at the MBA level divided between A’s and B’s. As such, you expect the mean GPA to be around 3.50. Using the sample of 200 MBA students, conduct a one-sample hypothesis test to determine if the mean GPA is different from 3.50. Use a .05 significance level.  Describe your findings which includes stating the hypotheses, direction of the test, p-value, decision to reject the null or not, and the conclusion. • PRACTICE PROBLEM 2:  Assume you read in the Concordia website that the average age of their MBA students is 45. Is this really true or have they failed to update this correctly?  You think it is far less because there have been a lot more students going straight from their Bachelors to their Masters since the economy is so bad.  You took a sample of 200 students (in the data file). Conduct a one-sample hypothesis test to determine if the mean age is less than 45. Use a .05 significance level.  Describe your findings which includes stating the hypotheses, direction of the test, p-value, decision to reject the null or not, and the conclusion.

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• PRACTICE PROBLEM 3: You have heard from idle chatter that 1 out of 5 students (20%) don’t declare a major. You took a sample of 200 students (in the data file). Conduct a one-sample hypothesis test to determine if the proportion without a major is greater than 20%. Use a .05 significance level. Describe your findings which includes stating the hypotheses, direction of the test, p-value, decision to reject the null or not, and the conclusion. Solutions are provided to practice problems so you can check your work.

 

 

Assigned Problems:  Top Colleges data (Submit by the end of Module 4) Use Top_Colleges.xls file which consists of data from 95 top-ranked colleges.  It includes variables regarding whether the college is public or private, the average annual out-of-state tuition & fees, and the average freshman SAT score (math + verbal only out of 1600). • ASSIGNED PROBLEM 1: For 2015, the average SAT score for incoming freshmen in the US was 1100.  Use the Hypothesis_Tests_One_Sample.xls file to test whether the top schools have an average SAT higher than the national average.  Use a .05 significance level.  Describe your findings which includes stating the hypotheses, direction of the test, p-value, decision to reject the null or not, and the conclusion. • ASSIGNED PROBLEM 2: It is commonly believed that while public schools typically have tougher admission standards, private schools are often better academically. Use the Hypothesis_Tests_One_Sample.xls file to test whether fewer than 50% of the top-ranked schools are public.  Use a .05 significance level.  Describe your findings which includes stating the hypotheses, direction of the test, p-value, decision to reject the null or not, and the conclusion.

 

Expectations:  Copy & paste the Excel displays into a Word file if you can. Upload the Word file (or the Excel files) for credit.  Comments in which you describe your findings should be included with each display.  APA formatting is not required for weekly assignments but adhere to the rules of written English in your punctuation, grammar and spelling.

 

Course Learning Outcomes: 1, 2, 3 & 4

Assignment #5: Multiple Sample Hypothesis Testing – 4 pts.  Due at the end of Module 5.

Practice Problems:  Student data (Do not submit) Use the Student.xls file for the following problems: • PRACTICE PROBLEM 1:  The battle of the sexes lives on still today. Since admission standards do not address gender whatsoever, there should be an equally diverse group of men and women in school, but do they perform equally well. Using the sample of 200 students, conduct a hypothesis test for two independent samples to determine if the mean MBA GPA differs for men and  women.  Use a .05 significance level.  Describe your findings. • PRACTICE PROBLEM 2:  Can a student keep up their grade performance at the next level? Is a strong GPA at the Bachelors level a good predictor of a strong GPA at the Masters level, or are GPAs naturally going to decline since graduate school is tougher, or will GPAs automatically be higher in graduate school because of the 3.00 requirement to graduate and the treatment of a C as subpar instead of average?  Using the sample of 200 students (in the data file), conduct a hypothesis test for paired samples and test if there is a difference in the mean GPA from the Bachelors to the Masters programs.  Use a .05 significance level.  Describe your findings.

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• PRACTICE PROBLEM 3: Given the reasons why people get their Masters, you surmise that men are more likely to declare a major than women. Using the sample of 200 students (in the data file), conduct a hypothesis test of proportions to determine if the proportion of women with “no major” is greater than the proportion of men with “no major”. Use a .05 significance level. Describe your findings. • PRACTICE PROBLEM 4: You have probably heard that if you want something done, give it to a busy person.  So is one’s employment status a factor in their academic performance?  Using the sample of 200 students (in the data file), conduct a hypothesis test using Analysis of Variance to determine if there is a difference in the mean GPA for those who are unemployed vs. work part- time vs. work full-time. Describe your findings. Solutions are provided to practice problems so you can check your work.

 

 

Assigned Problems:  Real Estate data (Submit by the end of Module 5) Use Real_Estate.xls file which consists of 100 homes purchased in 2015.  It includes variables regarding the number of bedrooms, number of bathrooms, whether the house has a pool or garage, the age, size and price of the home, what the house is constructed from, and the appraisals in 2014 and 2015. • ASSIGNED PROBLEM 1: It has been noted that swimming pools do nothing to increase value of a home.  Use the Hypothesis_Tests_Two_Samples.xls file to conduct a hypothesis test for two independent samples to determine if the mean sales differs for homes with and without a pool. Use a .05 significance level. Describe your findings which includes stating the hypotheses, direction of the test, p-value, decision to reject the null or not, and the conclusion.  Note that this requires an assumption that homes with a pool vs. those without are not much different otherwise (if those with a pool are in better locations, made of better materials, are newer and larger, then those homes will be worth more and it won’t have a thing to do with a pool.  So for the sake of simplicity, let’s assume that the homes with vs. without a pool have similar variability in them. • ASSIGNED PROBLEM 2: How different can two real estate agents be in their appraisals?  Use the Hypothesis_Tests_Two_Samples.xls file to conduct a hypothesis test for paired samples and test if there is a difference in the mean appraisal prices given by these agents on the same homes. Use a .05 significance level.  Describe your findings which includes stating the hypotheses, direction of the test, p-value, decision to reject the null or not, and the conclusion. • ASSIGNED PROBLEM 3: If people are going to spend a lot on their homes by constructing them out of brick, are they going to take the plunge and get a swimming pool too? Use the Hypothesis_Tests_Two_Samples.xls file to conduct a hypothesis test of proportions to determine if the proportion of homes made of brick are more likely to have a swimming pool vs. homes made of other materials.  Use a .05 significance level. Describe your findings which includes stating the hypotheses, direction of the test, p-value, decision to reject the null or not, and the conclusion.

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• ASSIGNED PROBLEM 4: You might expect that homes with more bedrooms are worth more since they are probably larger, but is there more to the value (like location, construction, age, etc.).? Using the sample of 100 homes (in the data file), conduct a hypothesis test using Analysis of Variance to determine if there is a difference in the mean sale price of homes with 2 bedrooms vs. 3 bedrooms vs. 4 bedrooms vs. 5 bedrooms. Use a .05 significance level. Describe your findings which includes stating the hypotheses, direction of the test, p-value, decision to reject the null or not, and the conclusion.  Since there are homes made of varying sizes at different locations and made of different material for this sample, it would be reasonable to assume that location and construction are not factors in this test.

 

Expectations:  Copy & paste the Excel displays into a Word file if you can. Upload the Word file (or the Excel files) for credit.  Comments in which you describe your findings should be included with each display.  APA formatting is not required for weekly assignments but adhere to the rules of written English in your punctuation, grammar and spelling.

 

Course Learning Outcomes: 1, 2, 3 & 4

Assignment #6: Chi Square Hypothesis Testing – 4 pts. Due at the end of Module 6.

Practice Problems:  Student data (Do not submit) Use the Student.xls file for the following problems: • PRACTICE PROBLEM 1:  Historically, the MBA program at Concordia has about 40% of their students choose a Leadership major, 30% choose a Finance major, 20% choose a Marketing major, and 10% choose no major.  Does the most recent class of 200 MBA students fit that same pattern or has there been a shift in the choice of majors. Using the sample of 200 students (in the data file), conduct a Chi Square Goodness of Fit test to determine if the current distribution fits the historical pattern. Use a .05 significance level.  Describe your findings. • PRACTICE PROBLEM 2:  While job opportunities for men and women are considerably more balanced than they were 40 years ago, the career aspirations may still differ. Is there a difference in majors chosen by men and women?  Using the sample of 200 MBA students (in the data file), conduct a Chi Square Test of Independence to determine if one’s choice of major is independent of their gender. Use a .05 significance level.  Describe your findings. Solutions are provided to practice problems so you can check your work.

 

Assigned Problems:  Guns data (Submit by the end of Module 6) Use Guns.xls file which consists of 50 states plus D.C. in 2010. It includes variables regarding the names of the states, whether the population density is relatively low / moderate / high, whether gun ownership by residents is relatively low / moderate / high, and whether murders committed by guns is relatively low / moderate / high. • ASSIGNED PROBLEM 1: In 2000, gun ownership in the U.S. had shown a decline from prior years, with about 10% of the states having high gun ownership, about 30% having moderate ownership, and about 60% having low ownership. Since then we have seen 9/11 and other terrorist acts as well as a lot of discussion about tightened gun control.  Using the Chi_Square.xls file, conduct a Chi Square Goodness of Fit test to determine if the 2010 distribution fits the pattern from a decade earlier.  Use a .05 significance level.  Describe your findings which includes stating the hypotheses, p-value, decision to reject the null or not, and the conclusion.

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• ASSIGNED PROBLEM 2: The argument for gun control is still brewing, with the main argument being that it either results in more or less gun-related deaths. Using the Chi_Square.xls file, conduct a Chi Square Test of Independence to determine if gun-related deaths are dependent on the prevalence of gun ownership. Use a .05 significance level. Describe your findings which includes stating the hypotheses, p-value, decision to reject the null or not, and the conclusion.

 

Expectations:  Copy & paste the Excel displays into a Word file if you can. Upload the Word file (or the Excel files) for credit.  Comments in which you describe your findings should be included with each display.  APA formatting is not required for weekly assignments but adhere to the rules of written English in your punctuation, grammar and spelling.

 

Course Learning Outcomes: 1, 2, 3 & 4

 

Assignment #7: Correlation & Regression – 4 pts. Due at the end of Module 7. Practice Problems:  Student data (Do not submit) Use the Student.xls file for the following problems: • PRACTICE PROBLEM 1:  Does undergraduate success predict graduate success? While most people complete their bachelor’s degree during the daytime while taking multiple classes and not working full-time, those getting an MBA are typically taking one or two courses at a time, in the evening or on weekends, and while working and even supporting a family. Yet one would expect those who perform better in their bachelor’s degree will perform better in their master’s. Using a significance level of .05, test whether there is a correlation between the BS GPA and the MBA GPA. Also, answer the following: a) Is the correlations statistically significant?  State the p-value. b) What is the correlation coefficient and how strong is it? c) What is the best fit regression equation that can predict the MBA GPA from the BS GPA? What does the coefficient in the regression equation mean (i.e., the number in front of BS GPA)? d) What percent of the variability in the MBA GPA can be explained by the regression model? e) What would you expect a student’s MBA GPA to be if he/she had a 3.50 BS GPA? • PRACTICE PROBLEM 2:  To get an even better model for predicting MBA performance, let’s look at many variables.  Create a multiple regression model predicting the MBA GPA using the BS GPA, the Hours studied per week, the Gender of the student, whether the student works full- time, and the student’s age. Use a .05 significance level.  After you create your model, predict the MBA GPA 40-year old student that studies 6 hours per week, works full-time, and had a 3.00 BS GPA. Solutions are provided to practice problems so you can check your work.

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Assigned Problems:  Baseball 2015 data (Submit by the end of Module 7) Use Baseball_2015.xls file which consists of 30 Major League Baseball teams’ statistics from 2015. It includes variables regarding the games played, wins & losses, at bats, runs scored, hits, homeruns, total bases, runs batted in, batting average, on base percentage, strikeouts, stolen bases, earned run average, saves, opponent runs, opponent batting average, errors, team payroll, the dollar value of each team win, and whether the team made it to the playoffs (FYI, Kansas City ultimately won the World Series). • ASSIGNED PROBLEM 1: A team must score more than their opponents to win a game, and so they must ultimately score runs since they cannot win with a score of zero. Are runs correlated with wins (i.e., does a team that scores more runs win more games)?  Use Correlation.xls to conduct a simple correlation analysis to determine if there is a correlation between Runs and Wins.  Use a .05 significance level.  Also answer the following: a) Is the correlations statistically significant?  State the p-value. b) What is the correlation coefficient and how strong is it? c) What is the best fit regression equation that can predict the Wins from the Runs? What does the coefficient in the regression equation mean (i.e., the number in front of Runs)? d) What percent of the variability in the Wins by the regression model? e) How many games would you expect a team to win if they scored 800 runs in a season? • ASSIGNED PROBLEM 2:  Let’s look at a popular argument that it takes money to win.  Well Kansas City had one of the lowest payrolls and won it all, Houston had the 2nd lowest payroll and made it far in the playoffs, and 7 of the top 10 payrolls didn’t even qualify for the playoffs. The evidence will show that money is not a predicting factor, but let’s make it official.  Use Correlation.xls to conduct a simple correlation analysis to determine if there is a correlation between Payroll and Wins. Use a .05 significance level.  Also answer the following: a) Is the correlations statistically significant?  State the p-value. b) What is the correlation coefficient and how strong is it? If the results are not statistically significant, you would normally stop at this point. • ASSIGNED PROBLEM 3: To get an even better model for predicting Wins, let’s look at many variables.  Create a multiple regression equation predicting the Wins using Runs, Hits, HomeRuns, Average, Strikeouts, Stolen Bases, and ERA. Use the Stepwise procedure to eliminate non-significant variables until the final equation has only significant variables.  After you create your regression equation, predict the Wins for a team that has 700 runs, 1500 hits, 200 homeruns, a .260 average, 1000 strikeouts, 100 stolen bases, and a 3.00 ERA.

 

Expectations:  Copy & paste the Excel displays into a Word file if you can. Upload the Word file (or the Excel files) for credit.  Comments in which you describe your findings should be included with each display.  APA formatting is not required for weekly assignments but adhere to the rules of written English in your punctuation, grammar and spelling.

 

Course Learning Outcomes: 1, 2, 3 & 4

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Assignment #8: Portfolio Assignment – 25 pts.  Due at the end of Module 8.

 

• Choose any published database from the internet (such as those from the Census Bureau or any financial or sports sites) or from your workplace. You may opt to use one of the data files provided by the instructor if applicable. • Your chosen database must be pre-approved by the instructor. • If the file is large than 200 observations, randomly choose 200 observations from the data. • Explain each variable in the file that you are analyzing. Be sure your file includes at least 3 scale variables and at least 2 nominal variables. • Conduct a descriptive analysis on any 2 interval / ratio variables you wish using Descriptive_Statistics.xls and Frequency_Distribution.xls. Explain the output. • Conduct 3 different hypothesis tests of your choice using appropriate variables from the file (note: you must use 3 different tests and not run one test on 3 different variables). In each case, state the variables being tested as well as the hypothesis, decision and conclusion. Use 3 of the following (1-Sample Test for Means, 1-Sample Test for Proportions, 2-Sample Test for Means – Independent Samples, 2-Sample Test for Means – Paired Samples, 2-Sample Test for Proportions, Analysis of Variance, Chi Square Goodness of Fit Test, Chi Square Test of Independence, Correlation Test). • Develop a model to predict an interval / ratio variable using at least 2 other variables. Use Multiple_Regression.xls and state the regression model and which variables are or are not significant. Also, use the model to make a prediction by making up values for each of the independent variables. • Write a one to two page summary of your findings. Include the data file in the appendix.

 

Expectations:  Copy & paste the Excel displays into a Word file if you can.  Upload the Word file (or the Excel files) for credit.  Comments in which you describe your findings should be included with each display.  APA formatting is not required but the assignment should be formatted professionally so that it flows well for weekly assignments and you should adhere to the rules of written English in your punctuation, grammar and spelling.

 

Course Learning Outcomes: 1, 2, 3 & 4

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Course Calendar

Module 1

Graphing & Descriptive Statistics

 

What is Statistics?  We use numbers every day to analyze the world or our piece of it, whether it be related to sports, finance, weather, politics, etc. Statistics is essentially a compilation of tools and techniques used for describing, organizing and interpreting these numbers; in other words, it is a means for converting data into information.  In the business world, there are four main uses of statistics  to summarize business data, to draw conclusions from that data, to make reliable forecasts, and to make decisions important to the business.  While it would be ideal if everyone could strive to be a doer of statistics, the aim here is for you to become an adept user of statistics.  Rather than trust headlines without substance, you might be able to see through the numbers and question results intelligently. You won’t just trust the media or politicians blindly. You can play fantasy sports with greater success.  You can make business decisions with facts and figures that you can interpret and not just with gut instinct.  Above all else, you will think differently and see the world in a way few people do.  In this module you will begin the journey to understanding Descriptive Statistics, which is the collecting, summarizing, presenting and analyzing of data sets.  Here we use tables, charts and graphs to display and picture the data, and we compute statistics to describe the data with single numbers.

 

Module Outcomes: A & D

Required Readings/Resources: Read the unit 1 lecture notes; watch the unit 1 video lecture.

 

Quiz:  Complete the unit 1 quiz, worth 3% of the course grade.  You may attempt it multiple times before the unit closes on Sunday night, with the highest score counting for your grade.  Each quiz consists of 12 random objective questions and there is a 30-minute time limit on each attempt.

 

Participation:  Complete the unit 1 discussions and activity for participation points, worth 3% of the course grade.

 

Discussion 1A (INTRODUCTIONS)  Tell us something about yourself. What has been your experience with Statistics? Why you are pursuing the MBA? What do you expect to learn from this course?  Feel free to share photos.

 

• Post a response to the question by Thursday, 11:59pm CST. • Comment to at least one other classmate by Sunday 11:59pm CST at the end of the week.

 

Discussion 1B (CHOOSING THE BEST MEASURE)  Suppose you applied to be a waiter or waitress at a local restaurant and asked the manager what a typical dinner shift was like. How might the manager describe the typical size of a party at a table? The mode would be useful, since there are a few repeated values. You might have an occasional table for 20, but, for the most part, parties

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consist of one to five people. What if you asked for the typical size of a check, so you could estimate your tips? The mode makes no sense, since you would not likely have many repeats, and the mean is easily distorted by that table for 20, but the median tells you that half the time you can expect to earn a certain amount of money in tips. Now suppose you were a real estate agent and you were asked by a client about the “typical” home in a subdivision. Being the astute agent you are, you have gathered the following information on each house in the subdivision: Price, square footage, numbers of bedrooms, number of bathrooms, and age. What statistic (mean, median, or mode) would you use to describe each aspect of the typical home and why?  Try to imagine the type of answers you would be giving your client based on your selections for a subdivision that has 100 homes with a wide variety of sizes and prices.

 

• Post a complete response to the question by Thursday, 11:59pm CST. • Given the nature of this question, no commenting to others is required for credit but is certainly welcome.

Discussion 1C (TRUSTING STATISTICS)  Do you always trust the statistics you see in print? How about the ones you hear on the news or on your favorite talk show? What makes the statistics credible?  For this question, I want you to tell me what personal criteria you would (or should) use to determine if you should believe reported statistics. Be specific, giving examples as needed.

 

• Post a complete response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

 

Refer to the MBA Discussions power point presentation for tips on how to gain maximum learning and points from your discussion engagement.

 

Activity 1: M&M Data Collection I suggest you get yourself a few bags of M&M’s for this course, as you will be doing some fun and tasty exercises with them. You could use the same bag each time, but who could resist eating them after you rip open the bag.

 

• The plain M&M’s Milk Chocolates are mass-produced with a distribution of 24% blue, 20% orange, 16% green, 14% yellow, 13% red and 13% brown. The peanut M&M’s are mass- produced with a distribution of 23% blue, 23% orange, 15% green, 15% yellow, 12% red and 12% brown. So choose your favorite, rip it open and spill them out (but don’t eat any yet).  Count how many (1a) blues, (2a) oranges, (3a) greens, (4a) yellows, (5a) reds and (6a) browns are in your package.  What percentage of the package are (1b) blues, (2b) oranges, (3b) greens, (4b) yellows, (5b) reds and (6b) browns? • Create a pie chart or bar chart showing the distribution.  Now you cannot expect your package to have exactly the same percentages as the population, but it probably will be similar. • After you report your totals, tell me whether you believe your package seems about right, and if not, what stands out (like there are hardly any greens or there are mostly reds). Now you can eat the evidence.

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• After each student has posted their results, the instructor will summarize the findings. This activity will count as part of the discussion grade, as the postings will be in the discussion forum.

 

• Post a complete response to each of the 12 questions by Friday, 11:59pm CST.

 

 

Module 2

 

Probability & the Normal Distribution

What comes to mind when you hear the word probability?  Most people think of gambling and it is understandable since you can never bet on a sure thing. But what is probability really?  It is the chance or likelihood of an event occurring. Whether you are deciding to take an umbrella because you just heard there would be a 50% chance of rain or you are making the decision to take another card in blackjack based on your total and a dealer’s up card or you are choosing which route to take home based on likely traffic from past experience, probability is a part of our daily lives.  We unknowingly use probability to make routine decisions, but a better understanding of the concepts could actually help in your making the best decisions. In this module you will explore the laws of probability and, in particular, learn how the normal probability distribution can be applied to solving countless types of problems with minimal data.

 

Module Outcomes: B & D

Required Readings/Resources: Read the unit 2 lecture notes; watch the unit 2 video lecture.

 

Quiz:  Complete the unit 2 quiz, worth 3% of the course grade.  You may attempt it multiple times before the unit closes on Sunday night, with the highest score counting for your grade.  Each quiz consists of 12 random objective questions and there is a 30-minute time limit on each attempt.

 

Participation:  Complete the unit 2 discussions and activity for participation points, worth 3% of the course grade.

 

Discussion 2A (SAMPLING VS. RELIABILITY) “The larger the sample, the more reliable the results.”  Do you agree or disagree with this statement?  Explain.

 

• Post a response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

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Discussion 2B (SEEING THROUGH THE CLAIM)  An auto manufacturer advertises that “90% of the cars we’ve ever made are still on the road.”  Assuming this is literally true, how can it be explained? What facts / statistics would you need to know to expose this misleading claim?

 

• Post a complete response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

 

Refer to the MBA Discussions power point presentation for tips on how to gain maximum learning and points from your discussion engagement.

 

Activity 2: M&M Probability Time to open another 1.69 ounce pack of M&M’s. Rip open a corner but don’t pour them out this time.  You are going to pour our several samples. The focus here is on the Blue candies. Approximately 1 out of every 4 in both the plain and peanut M&M’s are blue.

 

• 1st sample) Pour out 4 candies. (1) Count and record the total blues. Probability dictates that there should be 1 blue, but in a small sample anything can happen, and the results are random. • 2nd sample) Pour out 8 candies. (2) Count and record the total blues. Probability dictates that there should be 2 blues, but we shall see. • 3rd sample)  Pour out 12 candies.  (3) Count and record the total blues. Probability dictates that there should be 3 blues, and you are probably wondering why you are counting instead of eating. • 4th sample)  Pour out 16 candies.  (4) Count and record the total blues. Probability dictates that there should be 4 blues, and you can’t believe you are holding so many delicious candies in your hand at once. • 5th sample) There should be anywhere from 13 to 17 candies left in the package, so tell me (5a) how many were left and (5b) how many of them were blue. • Total package)  Add up your totals. (6a) How many candies were in the package and (6b) how many of them were blue. How close was it to one-fourth of the package? Were each of the samples consistent or did they vary a bunch? • In case you are wondering, you are burning calories while you are doing this mental exercise (hint, hint!). • After each student has posted their results, the instructor will summarize the findings. • This activity will count as part of the discussion grade, as the postings will be in the discussion forum.

 

 

• Post a complete response to each of the 8 questions by Friday, 11:59pm CST.

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Module 3

 

Confidence Intervals & Sample Sizes

 

Statistics means never having to say you’re certain.  Or at least that how it feels since we discuss everything in terms of probability and error. Remember that statistics are all about using samples to infer the truth about populations.  When we take a sample, we would love to believe that whatever is true about the sample is true about the population, but that will rarely ever happen, as there is almost always some difference (known as a margin of error or sampling error). Sampling is the essence of statistics. We normally cannot get access to an entire population and must make do with a sample, but we know that a sample is not exactly the same as the population.  There is going to be some difference between the results of a sample and the truth, and if we took another sample, the results would be different again. Ideally, we would like for the results of the sample to be relatively close to the truth, and for us to have confidence in the results.  Remember that the real objective in statistics can best be summarized in the definition of inferential statistics — using a sample to make inferences about a population.  In this module you will learn about why you should sample at all, the steps involved in proper sampling, the types of sampling, and the use of confidence intervals to estimate the truth about a population.

 

Module Outcomes: B & D

Required Readings/Resources: Read the unit 3 lecture notes; watch the unit 3 video lecture.

 

Quiz:  Complete the unit 3 quiz, worth 3% of the course grade.  You may attempt it multiple times before the unit closes on Sunday night, with the highest score counting for your grade.  Each quiz consists of 12 random objective questions and there is a 30-minute time limit on each attempt.

 

Participation:  Complete the unit 3 discussions and activity for participation points, worth 3% of the course grade.

 

Look at http://www.ncpp.org/?q=node/4 (20 Questions a Journalist Should Ask About Poll Results),  http://www.pollingreport.com (Polling Report) and http://www.realclearpolitics.com . Answer the following two questions.

 

Discussion 3A (SIZE VS. VALIDITY)  In evaluating a poll, a larger sample size would be considered more favorably, but what consideration would you consider even important than the sample size before trusting the validity of a poll?

 

• Post a response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

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Discussion 3B (POLLING RESULTS)  Choose any ONE of the polls from Polling Report. Compare the many polls used to address a single question and explain possible differences in results.

 

• Post a complete response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

 

Refer to the MBA Discussions power point presentation for tips on how to gain maximum learning and points from your discussion engagement.

 

Activity 3:  Sampling with Playing Cards • Take a standard deck of 52 playing cards.  Shuffle them well.  For our purposes, let’s assume the Ace is worth 1 point, 2 through 10 are worth their respective points, Jack is worth 11 points, Queen is worth 12 points, and King is worth 13 points. So there are 4 suits with values of 1 through 13 in them. The average value of all cards is 7.00. • Round 1) Deal the cards into 26 pairs.  Compute the averages of those 26 pairs.  It is possible to get two Aces, in which case the average is 1.00, and it is possible to get two Kings, in which case the average is 13.00.  Most likely the averages will tend to be in the 5 to 9 range. Report (1a) the lowest of your 26 averages, (1b) the highest of your 26 averages, (1c) how many of the 26 had an average between 6 and 8 inclusive (within 1 point of 7), and (1d) how many of the 26 had an average of exactly 7. • Round 2) Deal the cards into 13 piles of 4 cards.  Compute the 13 averages.  Report (2a) the lowest average, (2b) the highest average, (2c) how many of the averages were between 6 and 8 inclusive (within 1 point of 7), and (2d) how many averages were exactly 7. • Round 3) Deal the cards into 4 piles of 13 cards.  Compute the 4 averages. Report (3a) the lowest average, (3b) the highest average, (3c) how many of the averages were between 6 and 8 inclusive (within 1 point of 7), and (3d) how many averages were exactly 7. • After each student has posted their results, the instructor will summarize the findings. What we should see is that with samples of size 2, the averages will be spread out greatly, and only a few averages will be close to 7. And with samples of size 4, the spread of the averages will be greatly reduced, with almost every average being between 4 and 10, and most of them close to 7. Samples of size 13 should result in almost every one being close to 7 (although getting exactly 7 is less likely). • This activity will count as part of the discussion grade, as the postings will be in the discussion forum.

 

• Post a complete response to each of the 12 questions by Friday, 11:59pm CST.

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Module 4

 

One Sample Hypothesis Testing

 

How can we prove a coin is perfectly fair?  And can a doctor find you perfectly healthy? And can you prove your weight has not changed at all?  The answer is NO in all cases. We can never prove equality or lack of change, but we can find evidence to the contrary.  In medical tests, a physician looks for problems and in the absence of any being detected, they tell you that you tested negative and failed to find anything wrong with you.  With a coin, if you flip five heads and five tails, you are not convinced of anything regarding that coin; likewise if you flip nine heads and one tail, you are not convinced but are starting to get suspicious.  But if you flip 90 heads and 10 tails, you may rightly believe something is wrong, while 60 heads and 40 tails may not be quite enough to sway you.  When we have a theory about a parameter (the average is …, the proportion is …, etc.), we can test that theory via a hypothesis test.  If the results are far enough from the hypothesized number, we can conclude that with minimal error, the statement must be true.  If it isn’t far enough, we state that we just lack sufficient evidence to draw such a conclusion. Just like with weight loss, which is a form of a hypothesis test, we look for evidence (often in the form of data) to make our case, and then make a decision after reviewing the evidence.  In this module you will learn about the logic of hypothesis testing, the steps involved, and the ways it is used to draw conclusions with just a small sample.

 

Module Outcomes: C & D

Required Readings/Resources: Read the unit 4 lecture notes; watch the unit 4 video lecture.

 

Quiz:  Complete the unit 4 quiz, worth 3% of the course grade.  You may attempt it multiple times before the unit closes on Sunday night, with the highest score counting for your grade.  Each quiz consists of 12 random objective questions and there is a 30-minute time limit on each attempt.

 

Participation:  Complete the unit 4 discussions and activity for participation points, worth 3% of the course grade.

 

Discussion 4A (TRUSTING THE RESULTS)  If you were to read the results of a study showing that daily use of a certain exercise machine resulted in an average 10-pound weight loss, what more would you want to know about the numbers in addition to the average?  (Hint: Do you think everyone who used the machine lost 10 pounds?)

 

• Post a response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

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Discussion 4B (WHAT’S IN A SAMPLE?)  Why is it important that a sample be random and representative when conducting hypothesis testing?

 

• Post a complete response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

 

Refer to the MBA Discussions power point presentation for tips on how to gain maximum learning and points from your discussion engagement.

 

Activity 4: Hypothesis Testing with M&Ms • The plain M&M’s Milk Chocolates are mass-produced with a distribution of 24% blue, 20% orange, 16% green, 14% yellow, 13% red and 13% brown.  The peanut M&M’s are mass- produced with a distribution of 23% blue, 23% orange, 15% green, 15% yellow, 12% red and 12% brown. • Open a packet of your favorite M&Ms, plain or peanut. • Count the number of M&M’s in the packet. • Count number of BLUE, ORANGE, GREEN and RED candies. • Using the Excel file for One Sample Hypothesis Testing, conduct a test of proportions for each of the four colors. Use two-tailed tests and a .05 significance level in each case. Be sure to use the proportions shown above as the hypothesized values. • After each student has posted their results, the instructor will summarize the findings. What we should see is that about 5% of the samples will likely result in a rejection of the null hypothesis. • This activity will count as part of the discussion grade, as the postings will be in the discussion forum.

 

• Post a complete response for each of the 4 hypothesis tests by Friday, 11:59pm CST.

 

 

Module 5

 

Multiple Sample Hypothesis Testing

 

Suppose you wanted to know if men or women could do more sit-ups, or if homeschooled students do score better on SATs than those in a traditional classroom do, or if people with dogs tend to live longer than those without dogs.  In each case you can conduct a multiple sample hypothesis test to determine if a significant difference exists.  In the prior unit we looked at the logic of hypothesis testing and how a one-sample hypothesis test compares a sample to a hypothesized value to see if there is a significant difference.  Hypothesis testing in itself is a challenging concept to learn, but once it is embraced, it is far easier to learn about the different tests.  One of the biggest challenges researchers face is in deciding which hypothesis test technique to use; this requires answering four specific questions covered in this module.  Additionally, you will learn how to set up the data for different tests and to interpret results,

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Module Outcomes: C & D

Required Readings/Resources: Read the unit 5 lecture notes; watch the unit 5 video lecture.

 

Quiz:  Complete the unit 5 quiz, worth 3% of the course grade.  You may attempt it multiple times before the unit closes on Sunday night, with the highest score counting for your grade.  Each quiz consists of 6 random objective questions and there is a 30-minute time limit on each attempt.

 

Participation:  Complete the unit 5 discussions and activity for participation points, worth 3% of the course grade.

 

Discussion 5A (PROPORTIONALLY SPEAKING)  If a random sample of 10 people found that 9 were pro-life (i.e., 90%), while another random sample of 1000 people from the same population found that 550 were pro-life (i.e., 55%), which would you find to be more significant?  Why?

 

• Post a response to the question by Thursday, 11:59pm CST. • Given the nature of this question, no commenting to others is required for credit but is certainly welcome.

Discussion 5B (PROBING THE POLLSTERS)  When pollsters report results of a poll, they often include the margin of error but not much more.  If candidate X has 54% support of the voters with a margin of error of 3%, that means the candidate is predicted to have between 51% and 57% support in the election.  Before jumping to conclusions, what other information would you like the pollster to provide?

 

• Post a complete response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

 

Refer to the MBA Discussions power point presentation for tips on how to gain maximum learning and points from your discussion engagement.

 

 

Activity 5: Multiple Sample Hypothesis Testing with Playing Cards • Take a standard deck of 52 playing cards.  Separate the cards into 4 stacks by suit. For our purposes, let’s assume the Ace is worth 1 point, 2 through 10 are worth their respective points, Jack is worth 11 points, Queen is worth 12 points, and King is worth 13 points.  So there are 4 suits with values of 1 through 13 in them. The average value of all cards is 7.00. • From the Diamonds, remove the A, 2, 3 and 4; shuffle the rest of the stack and randomly choose 4 cards. • From the Hearts, remove the A, 2, Q and K; shuffle the rest of the stack and randomly choose 4 cards. • From the Clubs, remove the 10, J, Q and K; shuffle the rest of the stack and randomly choose 4 cards. • From the Spades, remove nothing; shuffle the entire stack and randomly choose 4 cards.

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• Using the Excel file for Analysis of Variance, conduct an ANOVA to test for a difference in the means for the four suits. Use a .05 significance level. If the null is rejected, be sure to look at the post hoc test results that follow. • After each student has posted their results, which will include the card values for each suit and the p-value, conclusion and post hoc results for the hypothesis test, the instructor will summarize the findings. What we should see is that many samples will probably show a significant  difference between the suits since the values are lower for some suits and higher for others. • This activity will count as part of the discussion grade, as the postings will be in the discussion forum.

 

• Post a complete response for each of the 4 hypothesis tests by Friday, 11:59pm CST.

 

 

Module 6

 

Chi Square Testing

 

Most hypothesis tests involve one variable being categorical in nature so we can analyze subgroups (e.g., scores for men vs. scores for women, with GENDER being the categorical variable).  In these parametric tests, the other variable must be a scale variable since the tests involve computing a mean.  Yet there are many occasions in which we have only categorical variables, and the technique is quite simple.  Its applications range from games of chance to analyzing surveys and polls.  In this module you will explore how to analyze patterns in strictly categorical data, determining if the distribution fits an expectation or determining if relationships exist between two variables.  Given the volume of polling done, especially during election years, you can truly grasp the meaning of the data beyond what is reported.

 

Module Outcomes: C & D

Required Readings/Resources: Read the unit 6 lecture notes; watch the unit 6 video lecture.

 

Quiz:  Complete the unit 6 quiz, worth 3% of the course grade.  You may attempt it multiple times before the unit closes on Sunday night, with the highest score counting for your grade.  Each quiz consists of 12 random objective questions and there is a 30-minute time limit on each attempt.

 

Participation:  Complete the unit 6 discussions and activity for participation points, worth 3% of the course grade.

 

Discussion 6A (PUTTING YOU ON) Many alleged studies are misleading in that the conclusions are often based on undisclosed premises.  Parenting books state that an advantage to breastfeeding is that it makes women healthier; what is not stated is that women who breastfeed tend to follow stricter diets, and it is the diets that actually makes them healthier.  If you looked at statistics for the number of tires replaced in a given year, would you be surprised to find out that Toyota Camry tops the list for wearing out tires? It shouldn’t since it is the most popular car in America.  And in 2000, Sen.

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Daschle (D-South Dakota) pushed his gun control agenda against Pres. Bush when he stated “Do you realize that the majority of vendors at gun shows don’t do background checks on their customers;” while true, what he failed to mention is that the majority of vendors at gun shows don’t sell guns (they sell food, t-shirts, souvenirs, etc.), but not guns.  Nonetheless, this quasi-truth aroused the voters. Name another conclusion that, while true, is based on misconception. There are multitudes of them in regards to health and politics, so keep your eyes open. If you cannot find one, then make one up (use your creativity and silliness if you wish).

 

• Post a response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

Discussion 6B (TRUTH IN ADVERTISING)  Infomercials often peddle products under the guise of “studies show…”. While some of the products are surprisingly good (e.g., FoodSaver, Foreman Grill, Ronco Rotisserie), many of the products are not.  Why should you be initially suspicious of any products advertised on these shows, despite the “existence” of data? What factors would help to convince you that the claims might be true?

 

• Post a complete response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

 

Refer to the MBA Discussions power point presentation for tips on how to gain maximum learning and points from your discussion engagement.

 

 

Activity 6:  Chi Square Goodness of Fit Testing with M&Ms • The plain M&M’s Milk Chocolates are mass-produced with a distribution of 24% blue, 20% orange, 16% green, 14% yellow, 13% red and 13% brown.  The peanut M&M’s are mass- produced with a distribution of 23% blue, 23% orange, 15% green, 15% yellow, 12% red and 12% brown. • Open a packet of your favorite M&Ms, plain or peanut. • Count the number of M&M’s in the packet. • Count number of BLUE, ORANGE, GREEN, YELLOW, RED and BROWN candies. • Using the Excel file for Chi Square Testing, conduct a Goodness of Fit test to determine if the distribution of colors in the package fits the expected distribution.  Use a .05 significance level.  Be sure to use the percentages shown above as the expected values. • After each student has posted their results (including the totals for each color and the p-value and conclusion for the hypothesis test, the instructor will summarize the findings. What we should see is that most, if not all, of the packages will fit the expected distribution, but with a small package of candy, anything is possible. • This activity will count as part of the discussion grade, as the postings will be in the discussion forum.

 

• Post a complete response for the ANOVA by Friday, 11:59pm CST.

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Module 7

Correlation & Regression

Did you know that there is a strong relationship between how many times each day that a mother burps her baby and the baby’s likelihood to get sick?  And if an infomercial sold a “Baby Burp Me” product, it would sell like hotcakes if mothers were convinced of this research that burping prevents illness. The key is that there is correlation, not causation. Mothers who burp their babies a lot are mothers who keep their babies at home instead of at a daycare, and it is the daycare which is the culprit.  So waking your baby up in the middle of the night to get extra burps in will not improve her health (but it might actually worsen it by messing with her sleep).  The burps are not the cause or a contributing factor and are merely circumstantial.  Correlation and regression are often misused or overused, but quite powerful tools when applied correctly, as you can determine relationships between variables, knowing if an increase in one variable corresponds with an increase or decrease in another. Think of the forecasting one can do with such a tool!  In this module you will learn about causation vs. correlation, the confusion that often occurs when variables are correlated, the meaning of regression models, and the stepwise technique used to determine the best predictive relationship between variables.

 

Module Outcomes: C & D

Required Readings/Resources: Read the unit 7 lecture notes.

 

Quiz:  Complete the unit 7 quiz, worth 3% of the course grade.  You may attempt it multiple times before the unit closes on Sunday night, with the highest score counting for your grade.  Each quiz consists of 10 random objective questions and there is a 30-minute time limit on each attempt.

 

Participation:  Complete the unit 7 discussions and activity for participation points, worth 3% of the course grade.

 

Discussion 7A (CORRELATION REVELATION) Regression and Correlation are the most used and most abused tools in research.  People are quick to jump to conclusions that if a relationship exists between two variables, then one must cause the other.  There are many reasons why two         variables can be related without causality.  For example, there is a strong inverse relationship between the sale of ice cream and the number of reported cases of the flu — does ice cream cure the flu?  Of course not, but more ice cream is consumed in the summer, when the flu is minimized, thus there is a seasonal relationship, not a causal one.  There is also a relationship between the seat belt lights turning on in an airplane and the existence of turbulence in flight, but the lights do not cause the turbulence.

 

Give a plausible explanation for the following correlations: • 1) There is a strong relationship between the amount of money people spend and the amount

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people save (in other words, people who spend more tend to save more).  Does this mean that you can improve your life savings by spending more money?  Explain how this correlation is true. • 2) There is a strong relationship between the number of cops on our streets and the number of reported crimes.  Does this mean that cops commit crimes or that criminals are more bold when cops are on the streets?  Explain how this correlation is true.

 

• Post a response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

 

 

Discussion 7B (JUMPING TO CONCLUSIONS) Name a situation in which a relationship exists in which people tend to jump to false conclusions about one variable causing the other.  There are many out there, so think hard.

 

• Post a complete response to the question by Thursday, 11:59pm CST. • Reply in a scholarly and substantive manner to at least one of your classmates by Sunday, 11:59pm CST at the end of the week.

 

Refer to the MBA Discussions power point presentation for tips on how to gain maximum learning and points from your discussion engagement.

 

 

Activity 7:  Correlation Testing of Ages • For today’s experiment, no candy or cards are needed. You just need to use what you already know (or you can take an educated guess). Think of at least 10 married couples you know. Write down their names. For each couple, write down the husband’s age followed by his wife’s age.  If you are not sure, you can ask them or just take an educated guess. • As long as you have at least 10 couples, you can proceed with the analysis; otherwise, keep thinking (and it could be people you just see at church or running the local store — you don’t have to know them well). • Using the Excel file for Correlation Analysis, conduct a Correlation test to determine if there is a correlation between a husband’s age and his wife’s age. Use a .05 significance level. Be sure to put the husband’s age in the left column (the Independent Variable) and the wife’s age in the right column (the Dependent Variable). • Is the correlation significant?  What is the correlation coefficient? What is the regression equation that predicts the wife’s age from the husband’s age? • After each student has posted their results (including the ages, p-value, correlation coefficient, and regression equation) the instructor will summarize the findings and combine the data to create a new correlation coefficient and regression equation. • This activity will count as part of the discussion grade, as the postings will be in the discussion forum.

 

• Post a complete response for the Correlation Analysis