MGS 8110 Applied Regression/Forecasting

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Presentation transcript:

MGS 8110 Applied Regression/Forecasting Overview

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

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

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

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

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