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variable at the speci ed level of con dence Accounts for multicolinearity (correlation between variables) Selects the most ef cient variables for the model, considering redundancy The method is programmable Stepwise regression is an algorithm that applies an iterative process to determine the optimal independent variables. For the rst step, all independent variables are entered into the model and are represented by their partial F statistic. A partial F statistic is the ratio of variance explained by the independent variable divided by total variation between all observations of the sample. An independent variable added at an earlier step may now be redundant because of the relationships between it and the independent variable now in the equations. If the partial F statistic for a variable is less than FOUT, the variable is dropped from the model. For this research, an FOUT corresponding to the 95 percent con dence level was used. Stepwise regression requires two cutoff variables, FIN and FOUT. Some analysts prefer FIN = FOUT, although this is not necessary. Frequently FIN > FOUT, making it relatively more dif cult to add an independent variable than to delete one (Montgomery, 2001). Minitab was applied to conduct this analysis. The F statistic is calculated based on the sum of squares from the regression results for each variable (the method discussed in the previous section determines the regression results). The mathematics for the F statistic is shown below. For multiple linear regression, the error and regression sum of squares take the same form as in the simple linear regression case (Walpole and Myers, 1993). The total sum of squares (SST) identity is SST = ( yi y )2 = ( yi y )2 + ( yi yi )2

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If you are chatting with someone who also has an iPhone 4 and is on Wi-Fi, you can tap the FaceTime icon to start a video call. (You may be able to use FaceTime on a 3G cellular connection in the future, but now, it requires a Wi-Fi connection.) You will see your picture in the top left portion of the window and your caller s picture in the main window. You will notice three buttons at the bottom: Mute, End call and Switch Camera to swap between your front-facing and rear-facing cameras. See 12: FaceTime Video Messaging and Skype for more on using FaceTime. NOTE: You will only see this FaceTime icon if your FaceTime is enabled (which you do in Settings Phone FaceTime set to ON).

Using a different notation for the SST identity: SST = SSR + SSE with SST = ( yi y )2 = total sum of squares

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There are k degrees of freedom associated with SSR and SST has n 1 degrees of freedom. Therefore, after subtraction, SSE has n k 1 degrees of freedom. The esti2 mate of is given by the error sum of squares divided by the degrees of freedom (Walpole and Myers, 1993). All three of the sums of squares appear on the printout of most multiple regression computer packages, including Minitab, which was used for this research. Minitab and SYSTAT were used to calculate these values. SYSTAT was used to verify results. The F statistic is calculated using the following equation: f = SSR/k SSR/k = SSE /(n k 1) s2

You can fine tune your email accounts on your iPhone with the myriad options available in the Settings app. Follow these steps to change these settings: 1. 2. Tap the Settings icon. Tap Mail, Contacts, Calendars.

Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright 2004 The McGraw-Hill Companies. All rights reserved. Any use is subject to the Terms of Use as given at the website.

The results of the sum of squares and F statistic may be represented in an analysis of variance (ANOVA) table (Table 16.2).

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The third phase LCA is aimed at evaluating the contribution to the impact categories speci ed in the scope and goal. In this phase, impact potentials are calculated based on the results from the inventory phase and are normalized and weighed based on the functional unit. Normalization provides a basis for comparing different types of environmental impact categories (all impacts get the same unit). Weighing implies assigning a weighing factor to each impact category depending on the relative importance.

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