# Multivariate Data Analysis Chapter 5 – Discrimination Analysis and Logistic Regression - PowerPoint PPT Presentation

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Multivariate Data Analysis Chapter 5 – Discrimination Analysis and Logistic Regression. MIS 6093 Statistical Method Instructor: Dr. Ahmad Syamil . Chapter 5. What Are Discrimination Analysis and Logistic Regression? Analogy with Regression and MANOVA

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Multivariate Data Analysis Chapter 5 – Discrimination Analysis and Logistic Regression

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## Multivariate Data AnalysisChapter 5 – Discrimination Analysis and Logistic Regression

MIS 6093 Statistical Method

### Chapter 5

• What Are Discrimination Analysis and Logistic Regression?

• Analogy with Regression and MANOVA

• Hypothetical Example of Discriminant Analysis

• A Two Group Discriminant Analysis: Purchasers Versus Nonpurchasers

• A Geometric Representation of the Two Group Discriminant Function

• A Three-group Example of Discriminant Analysis: Switching Intentions

### Chapter 5The Decision Process for Discriminant Analysis

• Stage 1: Objectives of Discriminant Analysis

• Stage 2: Research Design for Discriminant

Analysis

• Selection of Dependent and Independent Variables

• Sample Size

• Division of the Sample

• Stage 3: Assumptions of Discriminant

Analysis

### Chapter 5The Decision Process for Discriminant Analysis Cont.

• Stage 4: Estimation of the Discriminant Model

and Assessing Overall Fit

• Computation Method

• Statistical Significance

• Assessing Overall Fit

• Calculating Discriminant Z Score

• Evaluating Group Differences

• Assessing Group Membership Prediction Accuracy

• Casewise Diagnostics

• Misclassification of Individual Cases

• Summary

### Chapter 5The Decision Process for Discriminant Analysis Cont.

• Stage 5: Interpretation of the Results

• Discriminant Weights

• Partial F Values

• Interpretation of Two or More Functions

• Rotation of the Discriminant Functions

• Potency Index

• Which Interpretive Method to Use?

### Chapter 5The Decision Process for Discriminant Analysis Cont.

• Stage 6: Validation of the Results

• Split-Sample or Cross-Validation Procedures

• Profiling Group Differences

### Chapter 5

• Logistic Regression: Regression with a Binary Dependent Variable

• Representation of the Binary Dependent Variable

• Estimating the Logistic Regression Model

• Interpreting the Coefficients

• Assessing the Goodness-of-Fit of the Estimated Model

• Testing for Significance of the Coefficients

• Other Similarities To Multiple Regression

### Chapter 5A Two-group Illustrative Example

• Stage 1: Objectives of the Discriminant Analysis

• Stage 2: Research Design of the Discriminant

Analysis

• Selection of Dependent and Independent Variables

• Sample Size

• Division of the Sample

• Stage 3: Assumption of Discriminant Analysis

### Chapter 5A Two-group Illustrative Example Cont.

• Stage 4: Estimation of the Discriminant Function and

Assessing Overall Fit

• Estimation of the Discriminant Function

• Assessing Overall Fit

• Casewise Diagnostics

• Stage 5: Interpretation of the Discriminant

Function

• Stage 6: Validation of the Discriminant Results

• A Managerial Overview

### Chapter 5A Three-group Illustrative Example

• Stage 1: Objectives of the Discriminant Analysis

• Stage 2: Research Design of the Discriminant

Analysis

• Stage 3: Assumptions in Discriminant Analysis

• Stage 4: Estimation of the Discriminant Function

and Assessment

• Estimation of the Discriminant Functions

• Statistical Significance

• Assessing Overall Fit

• Casewise Diagnostics

### Chapter 5A Three-group Illustrative Example Cont.

• Stage 5: Interpretation of Three-group

Discriminant Analysis Results

• Rotation

• Assessing the Contribution of Predictor Variables

• Stage 6: Validation of the Discriminant

Results

• A Managerial Overview

### Chapter 5

• An Illustrative Example of Logistic Regression

• Summary

• Questions

• References

………end