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Chapter 16. Multiple Regression Analysis
Chapter 16. Multiple Regression Analysis
16.1 Introduction 448
16.1.1 Data Requirements for Multiple Regression 449
16.1.2 Multiple Regression Analysis Process 450
16.1.3 Multiple Regression Model 450
16.2 Detail Example: Profits of Bank Branches 451
16.3 JMP Analysis of Bank Branch Profits Example 453
16.3.1 Preliminary Fitting of Single X-Variables to Y 453
16.3.2 Fitting Several X-Variables to Y 456
16.3.3 What Dot-Ratios Measure? 459
16.3.4 Conclusion from the Three X-Variable Model 460
16.3.5 Regression Model Using Total Sales per Year = X1 and Total Sqft = X2 460
16.4 Evaluating Model Assumptions and Goodness of Fit 462
16.4.1 Residuals ei 462
16.4.2 Residuals ei and RMSE 463
16.4.3 Residuals and R2 464
16.4.4 R2 and RMSE 464
16.4.5 R2adj 465
16.4.6 Plot of Residuals versus Predicted Y (Yhat) or versus Time Order 465
16.4.7 Durbin-Watson Test for the Independence of Residuals 466
16.5 Model Interpretation 468
16.5.1 Leverage Plots and the Importance of Xi 469
16.5.2 Standardized Beta and the Importance of Xi 472
16.5.3 Understanding the Role of X-Variables: Column Diagnostics 473
16.6 Summary 475
16.7 Problems 476
16.8 Case Study: Forbes Global 2000 High Performers 479
16.9 References 480
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