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are often more useful than the ordinary residuals when assessing residual magnitude. The standardized residuals corresponding to e15 and e17 are d15 5.88 15.2352 2.57 and d17 4.33 14.2352 1.89, and they do not seem unusually large. Inspection of the data does not reveal any error in collecting observations 15 and 17, nor does it produce any other reason to discard or modify these two points. The residuals are plotted against y in Fig. 12-7, and against x1 and x2 in Figs. 12-8 and 12-9, respectively.* The two largest residuals, e15 and e17, are apparent. Figure 12-8 gives some indication that the model underpredicts the pull strength for assemblies with short wire length 1x1 62 and long wire length 1x1 152 and overpredicts the strength for assemblies with intermediate wire length 17 x1 142 . The same impression is obtained from Fig. 12-7.

*There are other methods, described in Montgomery, Peck, and Vining (2001) and Myers (1990), that plot a modified version of the residual, called a partial residual, against each regressor. These partial residual plots are useful in displaying the relationship between the response y and each individual regressor.

4. Before using XCopy to deploy a Web application, what must be done 5. What deployment method may be used to automatically restart the WWW service after the deployment has been completed

Figure 12-8

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In addition to changing the text s font and size, you can change its colour. You might do so to make the text better stand out against the background or to coordinate with colours used in other slide elements such as photographs. You can change the text colour using a number of methods. One is to select a colour from the Font Color button on the Home tab; another is to launch the Colors dialog box and select a colour from the palette that appears. In addition, you can apply your own custom colour to text.

Figure 12-9

1. Remove the word Set. 2. Add parentheses around Hello World. 3. The subprocedure must be enclosed in <script runat= server > tags. 4. The virtual directory must be created. 5. The Web setup project must be created.

In Example 12-9 we used the standardized residuals di ei 2 2 as a measure of residual magnitude. Some analysts prefer to plot standardized residuals instead of ordinary residuals, because the standardized residuals are scaled so that their standard deviation is approximately unity. Consequently, large residuals (that may indicate possible outliers or unusual observations) will be more obvious from inspection of the residual plots. Many regression computer programs compute other types of scaled residuals. One of the most popular is the studentized residual 2

Either the relationship between strength and wire length is not linear (requiring that a term 2 involving x1, say, be added to the model), or other regressor variables not presently in the model affected the response.

(12-42)

This appendix provides you with information on the contents of the Web site that accompanies this book. On this site, you will find information that will help you with each of the book s chapters. This Web site contains:

Thus H transforms the observed values of y into a vector of fitted values y. 31, xi1, xi2, p , xik 4 , Since each row of the matrix X corresponds to a vector, say x i another way to write the diagonal elements of the hat matrix is

(12-43)

Streaming video presentations that introduce you to each chapter of the book. These presentations are intended to provide late-breaking information that can help you understand the content of the chapter. Sample code that is used throughout the book. The sample code is presented as files with a .txt extension, which will allow you to easily copy and paste the code into your Visual Studio .NET project. The lab starter and lab solution for each chapter. The lab starter and solution is presented as a folder structure that can be unzipped and used as necessary. Bonus chapter.

Note that apart from 2, hii is the variance of the fitted value yi. The quantities hii were used in the computation of the confidence interval on the mean response in Section 12-3.2.

Under the usual assumptions that the model errors are independently distributed with mean zero and variance 2, we can show that the variance of the ith residual ei is V 1ei 2

Make sure that your computer meets the minimum system requirements listed in this section. If your computer doesn t match up to most of these requirements, you may have a problem using the contents of the Knowledge Publisher Studio.

hii 2,

2 3 A

Furthermore, the hii elements must fall in the interval 0 hii 1. This implies that the standardized residuals understate the true residual magnitude; thus, the studentized residuals would be a better statistic to examine in evaluating potential outliers. To illustrate, consider the two observations identified in Example 12-9 as having residuals that might be unusually large, observations 15 and 17. The standardized residuals are d15 Now h15,15 2 e15

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