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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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