Fundamentals of Predictive Analytics with JMP, Second Edition

Chapter 6: Logistic Regression

Introduction

Dependence Technique

The Linear Probability Model

The Logistic Function

A Straightforward Example Using JMP

Create a Dummy Variable

Use a Contingency Table to Determine the Odds Ratio

Calculate the Odds Ratio

A Realistic Logistic Regression Statistical Study

Understand the Model-Building Approach

Run Bivariate Analyses

Run the Initial Regression and Examine the Results

Convert a Continuous Variable to Discrete Variables

Produce Interaction Variables

Validate and Use the Model

Exercises

Introduction

Linear regression is designed for a continuous dependent variable, such as interest rates, budgets, and so on. Very often the dependent variable is not continuous, but discrete. There are many important situations ...