Probability statistics for engineers and scientists 9th by walpole myers chapter 12

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Probability  statistics for engineers and scientists 9th by walpole myers chapter 12

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Chapter 12 Multiple Linear Regression and Certain Nonlinear Regression Models Copyright © 2010 Pearson Addison-Wesley All rights reserved Section 12.1 Introduction Copyright © 2010 Pearson Addison-Wesley All rights reserved Section 12.2 Estimating the Coefficients Copyright © 2010 Pearson Addison-Wesley All rights reserved Table 12.1 Data for Example 12.1 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - Table 12.2 Data for Example 12.3 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - Section 12.3 Linear Regression Model Using Matrices Copyright © 2010 Pearson Addison-Wesley All rights reserved Table 12.3 Data for Example 12.4 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - Section 12.4 Properties of the Least Squares Estimators Copyright © 2010 Pearson Addison-Wesley All rights reserved Theorem 12.1 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - Section 12.5 Inferences in Multiple Linear Regression Copyright © 2010 Pearson Addison-Wesley All rights reserved Figure 12.5 R-Student values plotted against predicted values for grasshopper data of Case Study 12.1 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 28 Section 12.11 Cross Validation, Cp, and Other Criteria for Model Selection Copyright © 2010 Pearson Addison-Wesley All rights reserved Table 12.12 Data Set Case Study 12.2 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 30 Table 12.13 Comparing Different Regression Models Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 31 Table 12.14 PRESS Residuals Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 32 Table 12.15 Data for Example 12.12 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 33 Figure 12.6 SAS printout of all possible subsets on sales data for Example 12.12 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 34 Figure 12.7 Normal probability plot of residuals using the model x1x2x3 for Example 12.12 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 35 Section 12.12 Special Nonlinear Models for Nonideal Conditions Copyright © 2010 Pearson Addison-Wesley All rights reserved Figure 12.8 The logistic function Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 37 Table 12.16 Data Set for Example 12.13 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 38 Definition 12.1 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 39 Figure 12.9 SAS output for Review Exercise 12.72; part I Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 40 Figure 12.10 SAS output for Review Exercise 12.72; part II Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 41 Section 12.13 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters Copyright © 2010 Pearson Addison-Wesley All rights reserved ... Data for Example 12. 1 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - Table 12. 2 Data for Example 12. 3 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - Section 12. 3... AddisonWesley All rights reserved 12 - 18 Table 12. 7 Data for Example 12. 9 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 19 Figure 12. 3 SAS printout for Example 12. 9 Copyright © 2010 Pearson... All rights reserved 12 - 26 Table 12. 11 Residual Information for the Data Set for Case Study 12. 1 Copyright © 2010 Pearson AddisonWesley All rights reserved 12 - 27 Figure 12. 5 R-Student values

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  • Slide 1

  • Slide 2

  • Slide 3

  • Table 12.1 Data for Example 12.1

  • Table 12.2 Data for Example 12.3

  • Slide 6

  • Table 12.3 Data for Example 12.4

  • Slide 8

  • Theorem 12.1

  • Slide 10

  • Figure 12.1 SAS printout for data in Example 12.4

  • Slide 12

  • Slide 13

  • Table 12.4 Analysis of Variances for Orthogonal Variables

  • Table 12.5 Data for Example 12.8

  • Table 12.6 Analysis of Variance for Grain Radius Data

  • Slide 17

  • Figure 12.2 Case of three categories

  • Table 12.7 Data for Example 12.9

  • Figure 12.3 SAS printout for Example 12.9

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