| Course ID: | BUSN 4000. 3 hours. |
| Course Title: | Predictive Modeling and Optimization |
Course
Description: | Focuses on calculus, statistical inference, predictive
modeling, and optimization. Special attention will be given to
the foundations of these topics and also to the modeling and
application of these tools within all the functional areas of
business. |
| Oasis Title: | Predictive Model Optimization |
| Duplicate Credit: | Not open to students with credit in BUSN 4000E, BUSN 4000H |
| Prerequisite: | MSIT 3000 or MSIT 3000E or MSIT 3000H or BUSN 3000 or BUSN 3000E or BUSN 3000H |
| Grading System: | A-F (Traditional) |
|
| Course Objectives: | A student who completes this class will be able to:
1. recognize the principles that underlie causal inference.
2. employ statistical methods to predict organizational and
market outcomes.
3. apply the concept of the derivative to determine optimal
outcomes. |
| Topical Outline: | Review of Foundations (2 wks)
• Descriptive Statistics
• Inferential Statistics
• The Simple Linear Regression Model
• Review of Functions - Linear, Quadratic, Exponential,
and Logarithmic Functions (etc.)
Predictive Modeling – Regression (8-9 wks)
• Data Structures
• The Experimental Idea
• Model Specification
• Regression and Causality
• Estimation and Inference
• Regression with Qualitative Data
• Application of Regression Models
• Propensity Score Matching
Mathematics of Change and Optimization (4-5 weeks)
• The Derivative
• Rules for Differentiation
• Derivative as a Rate of Change
• Higher Order Derivatives
• Partial Derivatives
• Using the Derivative
o Local and Global Maxima and Minima
o Inflection Points
o Profit, Cost and Revenue
o Elasticity of Demand
o Optimization Problems |