1. MGS 8110 Applied Regression/Forecasting
Overview

2. Decision Making Environment Challenge Solutions Uncertainty Complexity
Equivocality
Lack of information
Fuzzy data, inability to access
Too much information, disorganized
Lack of expertise, inability to interpret, multiple interpretations
Data Based Systems
Model Based systems, Analytics
Expert Systems, AI

3. Analytics in Business Past Present Future Information Reports Alerts
Extrapolation
Insight
Regression Models
Recommenda-tions, DSS
Simulations
Source: “Analytics at Work: Smarter Decisions, Better Results” by Davenport, Harris, & Morison

4. Course Outline: Time Series Analysis
Goal: Examining patterns over time, projecting forward
Data
Technique
No Trend
Trend
Linear
Non-linear
Seasonality
Heuristic (averaging)
Line fitting
Linear function
Quadratic, Log functions
Classical Decomposition

5. Course Outline: Regression Analysis
Goal: Examining relationships between variables, using values of some (independent) variables to understand and/or predict the values of other (dependent) variables.
Data
Technique
One independent
2+ independent
Special Cases:
Categorical data
Interactions
Simple Regression
Multiple Regression
Dummy Variables
Interaction Terms