Probability statistics for engineers and scientists 9th by walpole myers chapter 11

Chapter 11 Simple Linear Regression and Correlation Copyright © 2010 Pearson Addison-Wesley All rights reserved Section 11.1 Introduction to Linear Regression Copyright © 2010 Pearson Addison-Wesley All rights reserved Figure 11.1 A linear relationship; 0: intercept; 1: slope Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - Section 11.2 The Simple Linear Regression (SLR) Model Copyright © 2010 Pearson Addison-Wesley All rights reserved Figure 11.2 Hypothetical (x,y) data scattered around the true regression line for n = Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - Table 11.1 Measures of Reduction in Solids and Oxygen Demand Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - Figure 11.3 Scatter diagram with regression lines Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - Figure 11.4 Individual observations around true regression line Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - Section 11.3 Least Squares and the Fitted Model Copyright © 2010 Pearson Addison-Wesley All rights reserved Figure 11.5 Comparing i with the residual, ei Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 10 Section 11.11 Simple Linear Regression Case Study Copyright © 2010 Pearson Addison-Wesley All rights reserved Table 11.8 Density and Stiffness for 30 Particleboards Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 43 Figure 11.23 Scatter plot of the wood density data Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 44 Figure 11.24 Residual plot for the wood density data Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 45 Figure 11.25 Normal probability plot of residuals for wood density data Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 46 Section 11.12 Correlation Copyright © 2010 Pearson Addison-Wesley All rights reserved Figure 11.26 Residual plot using the log transformation for the wood density data Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 48 Figure 11.27 Normal probability plot of residuals using the log transformation for the wood density data Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 49 Table 11.9 Data on 29 Loblolly Pines for Example 11.10 Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 50 Figure 11.28 Scatter diagram showing zero correlation Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 51 Figure 11.29 SAS printout, showing partial analysis of data of Review Exercise 11.54 Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 52 Figure 11.30 SAS printout, showing partial analysis of data of Review Exercise 11.55 Copyright © 2010 Pearson AddisonWesley All rights reserved continued on next slide11 - 53 Figure 11.30 SAS printout, showing partial analysis of data of Review Exercise 11.55 (cont’d) Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 54 Figure 11.31 SAS printout, showing residual plot of Review Exercise 11.55 Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 55 Section 11.13 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters Copyright © 2010 Pearson Addison-Wesley All rights reserved ... reserved 11 - 20 Figure 11. 12 Confidence and prediction intervals for the chemical oxygen demand reduction data; inside bands indicate the confidence limits for the mean responses and outside bands... Addison-Wesley All rights reserved Figure 11. 7 MINITAB printout for t-test for data of Example 11. 1 Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - 15 Figure 11. 8 The hypothesis H0: 1 = is... around the true regression line for n = Copyright © 2010 Pearson AddisonWesley All rights reserved 11 - Table 11. 1 Measures of Reduction in Solids and Oxygen Demand Copyright © 2010 Pearson AddisonWesley