MGG 633 Modeling Managerial Processes

Managerial activity revolves around the decision making. Many consider decision making to be an art; something learned by trial and error; something based on creativity, judgment, intuition, and experience rather than anything that may be subjected to systematic analysis. This course provides an introduction to the concepts and methods of Decision Science, which involves the application of mathematical modeling and analysis to managerial problems. It provides a structured way of attacking a wide range of real problems, using data-driven analysis to guide decision making. 

The primary goal of the course is to help students to become a more skilled builder and consumer of models and model-based analyses. Specifically the purposes of this course are to:

  • Introduce you to the basic principles and techniques of applied mathematical modeling for managerial decision-making.
  • Sharpen Students ability to structure problems and to perform logical analyses.
  • Expose students to settings in which models can be used effectively.
  • Strengthen students computer skills by illustrating the use of computing technology to model problems in various functional areas.
  • Exploit the computer as a resource in analyses and a tool in support of decision making.

MGG 619 & MGG 620 Developing Emotional Intelligence

Orientation and Objective:

Success in today’s organizations depends on your ability to learn and adapt quickly to new and changing situations.  The objective of this course is therefore to prepare students to be life-long adapters.  The course is based on a model of self-directed learning and development.  This process will help students throughout their careers in understanding and formulating their own vision, in assessing their skills and abilities and designing plans to reach their objectives.  From mastery of this basic process comes the ability to lead others effectively. Overall, the course is intended:

  • To use the expertise of MBA students in contributing actively and directly to the learning process
  • To have you identify personal limitations and establish a developmental plan to identify those areas you are interested in changing
  • To create individualized development plans for executives
  • To enhance the ability of MBA students to participate in a non-hierarchical team environment
  • To improve the leadership skills of MBA students throughout the program
  • To provide a forum for interaction between MBA students and senior executives from the business community


Orientation and Objective:

All managerial activities revolve around the making of decisions. This course introduces the concepts and methods of quantitative and statistical analysis. One essential aspect of decision making involves organizing and evaluating relevant information. Quantitative methods generally, and statistical methods specifically, have value for managers because they provide approaches for organizing, evaluating and interpreting information important to managerial decisions. Given the amount of data accessible to today’s managers there is an increasing need to rely on statistical methods as a means of extracting significant information and giving it meaning. Statistical methods provide an organized and structured way of looking at and thinking about disorganized, unstructured appearing phenomena.

The major objective for this course is to increase your ability to think statistically and combine those concepts with managerial thinking to assist you in decision making. To facilitate this it is designed to acquaint students with those statistical tools useful to the commonly encountered business problems. Management applications using case studies/examples and computer applications are emphasized! We will be emphasizing the use of a spreadsheet software package (Microsoft Excel) as an important tool for quantitative analysis.

Course Topics

  • Description (data analysis, summary, and display): Descriptive Statistics coverage includes graphical displays, central tendency, and variation.

  • Analyses of Qualitative Data:  Proportions (Percentages), Contingency Tables

  • Probability (understanding chance and uncertain events): Probability will cover the basic laws of probability, random variables and distribution including both the Binomial and Normal.

  • Statistical inference (discovery of the hidden structure of observed data): Inference will consider hypothesis testing, estimation and confidence intervals used to draw conclusions from data.

  • Prediction:  Simple and Multiple Regression Models


MGQ 606 MGG 633 EQ