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
- 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
MGG 619 & MGG 620 Developing Emotional Intelligence
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
provide a forum for interaction between MBA students and senior
executives from the business community
MGQ 606: PROBABILITY AND STATISTICS FOR MANAGEMENT
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
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, summary, and display): Descriptive Statistics coverage
includes graphical displays, central tendency, and variation.
Analyses of Qualitative
Data: Proportions (Percentages), Contingency Tables
(understanding chance and uncertain events): Probability will cover the
basic laws of probability, random variables and distribution including
both the Binomial and Normal.
(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