MBA 633 Master Syllabus

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MBA 633: Statistics for Business Decision Making Master Syllabus


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MBA Program Learning Goals

The MBA program focuses on the following program learning goals:  

  • Teaming & Leading - Our graduates will demonstrate the team leadership and interpersonal skills needed to form, lead, and work effectively on diverse organizational teams. 
  • Analytical Decision Making - Our students will demonstrate the ability to analyze uncertain complex management situations using appropriate tools, techniques, and information systems for decision-making. 
  • Knowledge of Functional Business Disciplines- Our graduates will demonstrate the ability to integrate knowledge from all functional areas of business into a meaningful firm-level perspective 
  • Global Understanding - Our graduates will demonstrate a perspective on how businesses operate in the global environment. 
  • Communication Skills - Our graduates will demonstrate written, oral and presentations skills necessary to explain problems and solutions effectively and persuasively. 
  • Ethics and Social Responsibility - Our graduates will have a sense of professional and social responsibility in the conduct of managerial affairs. 

Course Objectives

The main objectives of this course are to provide the student with the ability to: 

  1. Understand and apply statistical techniques in describing and analyzing data; 
  2. Apply statistical analysis for inference, prediction, and decision making; 
  3. Understand and detect flaws in statistical reports and analysis; 
  4. Identify statistical tools for specific managerial applications 
  5. Use MS-Excel to perform statistical analysis. 

Grading Scheme (Subject to Change)

Individual Case Studies 40%
Assignments 30%
Final Exam  30%
Total 100%

Assignments/Case Analysis

There will be several home assignments (to be done individually), and mini-case studies (both group and individual) assigned in class. Students are expected to solve all assigned problems and case studies, which will be collected on their due dates and graded. 

Both class assignments and case analyses are an important component of the learning process, and each assignment/case must be turned in no later than its due date.   Individual assignments are to be solved individually with no assistance from anyone. 


Recommendations

  • This course has a large amount of quantitative content.  The best way to master the material is to solve as many problems as you can.   
  • Bring your textbook and laptops to every class.  We will work lots of problems in class and you will learn more from those exercises if you have the software to handle the number crunching. 
  • Be sure to compare your homework answers to the solutions provided in class and understand any mistakes you may have made. 
  • Statistics is in use all around you.  Keep a lookout for applications of statistical concepts and data in what you read, hear and do on a daily basis. This will strengthen your understanding of core concepts. 
  • Keep up with readings.  Concepts will build on one another rather rapidly. 

Course Grading

90% and above A/A- (split to be decided by instructor based on clustering)
80% to < 90% B+/B/B- (split to be decided by instructor based on clustering)
70% to < 80% C  
<70% F  

George Mason Email Accounts

Students must use their George Mason email accounts to receive important University information, including messages related to this class. See Mason Email website for more information. 


Academic Integrity

This course is conducted in accordance with the George Mason Honor Code.  Students are obligated to strict adherence to the University honor system and code.

The principle of academic integrity is taken very seriously and violations are treated gravely. What does academic integrity mean in this course? Essentially this: when you are responsible for a task, you will perform that task. In all your assignments and exams, keep in mind that you may not present as your own the words, the work, or the opinions of someone else without proper acknowledgement. When you rely on someone else’s work in an aspect of the performance of that task, you will give full credit in the proper, accepted form.  

(Costello College of Business Recommendations for Honor Code Violations will be followed). 


School of Business Standards of Behavior

The mission of the School of Business at George Mason University is to create and deliver high quality educational programs and research. Students, faculty, staff, and alumni who participate in these educational programs contribute to the well-being of society. High quality educational programs require an environment of trust and mutual respect, free expression and inquiry, and a commitment to truth, excellence, and lifelong learning. Students, program participants, faculty, staff, and alumni accept these principles when they join the School of Business community. In doing so, they agree to abide by the following standards of behavior:  

  • Respect for the rights, differences, and dignity of others  
  • Honesty and integrity in dealing with all members of the community  
  • Accountability for personal behavior  

Integrity is an essential ingredient of a successful learning community. Ethical standards of behavior help promote a safe and productive community environment, and ensure every member the opportunity to pursue excellence.  School of Business can and should be a living model of these behavioral standards. To this end, community members have a personal responsibility to integrate these standards into every aspect of their experience at the  School of Business. Through our personal commitment to these Community Standards of Behavior, we can create an environment in which all can achieve their full potential. 


Other Useful Campus Resources

Office of Disability Services
If you are a student with a disability and you need academic accommodations, please see me and contact the Student Disability Resource Center at (703) 993-2474. All academic accommodations must be arranged through the ODS. 

University Libraries 
“Ask a Librarian” 

Counseling and Psychological Services (CAPS)
Website
(703) 993-2380 

Inclement Weather & Campus Emergencies
Information regarding weather related changes in the University’s schedule (e.g., closing or late opening) will be provided on the George Mason website and via MasonAlert. I plan to hold class unless the campus is officially closed. If class is cancelled due to inclement weather or other emergency, activities (e.g., coverage of material, exams, etc.) scheduled for that class will normally be moved to the next class. We will discuss further changes when we meet. 

University Policies
The University Catalog, is the central resource for university policies affecting student, faculty, and staff conduct in university academic affairs. Other policies are available here. All members of the university community are responsible for knowing and following established policies. . 

Safe Return to Campus Statement
Students have to follow George Mason’s Covid related policies.


MBA 633 Course Topics

Note: The schedule given in the next page is tentative and may be subject to change. 

Topics

Introduction to Course  
Course Overview  
Descriptive Statistics:  
Tabular and Graphical Methods  

Numerical Measures 
Measures of Location and Measures of Variability 
Measures of Relative Location, z-scores 
Empirical Rule 
Exploratory Data Analysis 

Introduction to Probability  

Random Variables 
Discrete Probability Distributions 
Expected Value and Variance  

Continuous Probability Distributions 
Normal Distribution 

Sampling Distributions  

Point Estimation 
Central Limit Theorem 

Interval Estimation 
Confidence Intervals for Population Means,  
t – Distribution
Hypothesis Testing 
Null and Alternative Hypotheses, One-Tail and Two-Tail tests 
Significance Levels, p-values 
Inferences about Means from Two Populations 
Null and Alternative Hypotheses, One-Tail and Two-Tail tests 
Significance Levels, p-values 
Inferences about Two Population Variances 
Null and Alternative Hypotheses, F-distribution 
Significance Levels, p-values 

Simple Linear Regression and Correlation  

  • Correlation Coefficient 
  • Regression Notation 
  • Least Squares method 
  • Coefficient of Determination 
  • Adjusted Coefficient of Determination 
  • Computer Solution/Interpretation 
  • Testing for Significance, Model Verification 
  • Estimation and Prediction 

Multiple Regression 

  • Correlation Coefficient 
  • Regression Notation 
  • Least Squares method 
  • Coefficient of Determination 
  • Adjusted Coefficient of Determination 
  • Computer Solution/Interpretation 
  • Testing for Significance, Model Verification 
  • Estimation and Prediction  
Final Exam

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