MBA Course in Business Statistics

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Jamal Munshi PhD, All rights reserved

The course
Successful managers make decisions under undertainty and manage risk. They do that by extracting useful and unbiased information from all available data. Statistics gives them the tools to carry out this function. This course prepares them for this role. It presents probability theory, hypothesis testing, and regression to the student within this management context. Students are expected to have completed a course in the fundamentals of statistics in undergraduate school. The course is quantitative in nature and it requires proficiency in mathematics and in Microsoft Excel. Proficiency in written English is also important. Please bring your notebook computer to class with PHSTAT installed and all data files pre-loaded.
Textbook
David M. Levine et al, Statistics for Managers
Prentice Hall, link, ISBN 0131249614
To prepare for the course, students are expected to read Chapters 1 through 7 on their own as a review of statistics fundamentals.
Classroom activities
There are 8 class meetings on 8 consecutive weeks, one day per week, and one scheduled final examination period.
There may be up to three activities per meeting
Activity #1: Quiz on previous topic: 1 hour
Activity #2: Lecture on new topic: 1.5 hours
Activity #3: Workshop on new topic: 1.5 hours
Meeting #1
Workshop #1: Hypothesis testing basics
To prepare for workshop #1 please read chapter 8
Meeting #2
Quiz #1: Hypothesis testing basics
To prepare for quiz #1 review your work in workshop #1
Workshop #2: Comparison of sample means
To prepare for workshop #2 please read chapter 9
Meeting #3
Quiz #2: Comparison of sample means
To prepare for quiz #2 review your work in workshop #2
Workshop #3: Analysis of variance
To prepare for workshop #3 please read chapter 10
Meeting #4
Quiz #3: Analysis of variance
To prepare for quiz #3 review your work in workshop #3
Workshop #4: Non-parametric statistics
To prepare for workshop #4 please read chapter 11
Meeting #5
Quiz #4: Non-paremetric statistics
To prepare for quiz #4 review your work in workshop #4
Workshop #5: Simple linear regression
To prepare for workshop #5 please read chapter 12
Meeting #6
Quiz #5: SLR
To prepare for quiz #5 review your work in workshop #5
Workshop #6: Multiple regression
To prepare for workshop #6 please read chapter 13
Meeting #7
Quiz #6: Multiple regression
To prepare for quiz #6 review your work in workshop #6
Workshop #7: Special topics in multiple regression
To prepare for workshop #7 please read chapter 14
Meeting #8
Quiz #7: Special topics in multiple regression
To prepare for quiz #7 review your work in workshop #7
Workshop #8: Time series analysis
To prepare for workshop #8 please read chapter 15
Scheduled final examination period
Quiz #8: Time series analysis
To prepare for quiz #8 review your work in workshop #8
Semester project
Submit a solution to the chapter 17 problem that was assigned to your group along with a case study of the implementation of six-sigma management in Thailand. Report and presentation are required.
Assignment types
The class is divided into groups. Workshops and semester projects are group assignments. They are carried out cooperatively by group members working as a team. The instructor serves as an ex-officio member of each group. Quizzes and examinations are individual assignements. Please do these on your own. You are expected to complete your quiz without using your book or notes. Please turn in your workshop before you take the quiz. For group assignments submit one paper per group. For individual assignments submit one paper per student.
Missed workshops and quizzes
Once per term, the student may carry the weight of a missed workshop forward to the next workshop. Once per term, the student may carry the weight of a missed quiz forward to the next quiz. There is no provision for make-up workshops or quizzes. There is no remedy for missing the last workshop or quiz.
Evaluation of learning
8 Workshops x 4 points each = 32 points
8 In-class short quizzes x 8 points each = 64 points
Semester project = 4 points
Total = 100 points
Letter grade: 90-100 = A, 80-90 = B, 75-80 = B-, 60-75 = D, else F
Outcomes
After completing this course you should be able to
  • use hypothesis testing to evaluate means, proportions, and their differences
  • state the assumptions of hypothesis testing and the consequences of their violation
  • describe the concept of experimental design and apply this concept in one-way and factorial design ANOVA
  • apply non-parametric statistics in business management with particular reference to chi-square, Wilcoxon, and Kruskal-Wallis
  • apply simple linear regression in making business decisions
  • state the assumptions of SLR and the consequences of their violation
  • make inferences about regression parameters and apply them to business management
  • develop and apply multiple regression models for business
  • use dummy variables in multiple regression models
  • state the assumptions of multiple regression and the consequences of their violation
  • make inferences about multiple regression model parameters
  • describe time series models and their application in business forecasting with particular reference to moving averages, exponential smoothing, and autoregressive models
  • state the assumptions of time series models and the consequences of their violation
  • apply statistical principles in quality control using TQM, six-sigma, and control charts

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