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Multivariate Data Analysis Chapter 5 – Discrimination Analysis and Logistic Regression

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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  1. Multivariate Data AnalysisChapter 5 – Discrimination Analysis and Logistic Regression MIS 6093 Statistical Method Instructor: Dr. Ahmad Syamil

  2. 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

  3. 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

  4. 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

  5. Chapter 5The Decision Process for Discriminant Analysis Cont. • Stage 5: Interpretation of the Results • Discriminant Weights • Discriminant Loadings • Partial F Values • Interpretation of Two or More Functions • Rotation of the Discriminant Functions • Potency Index • Graphical Display of Discriminant Loadings • Which Interpretive Method to Use?

  6. Chapter 5The Decision Process for Discriminant Analysis Cont. • Stage 6: Validation of the Results • Split-Sample or Cross-Validation Procedures • Profiling Group Differences

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. Chapter 5 • An Illustrative Example of Logistic Regression • Summary • Questions • References ………end

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