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TABLE 14-11 A Weight-Loss Clinic Wants to Use Regression Analysis to Build

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TABLE 14-11
A weight-loss clinic wants to use regression analysis to build a model for weight-loss of a client (measured in pounds) . Two variables thought to affect weight loss are client's length of time on the weight loss program and time of session. These variables are described below:
TABLE 14-11 A weight-loss clinic wants to use regression analysis to build a model for weight-loss of a client (measured in pounds) . Two variables thought to affect weight loss are client's length of time on the weight loss program and time of session. These variables are described below: Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model: Partial output from Microsoft Excel follows: Regression Statistics ANOVA -Referring to Table 14-11, in terms of the β's in the model, give the average change in weight-loss (Y) for every 1 month increase in time in the program (X<sub>1</sub>) when attending the evening session. A) β<sub>1 </sub>+ β<sub>4</sub> B) β<sub>1 </sub>+ β<sub>5</sub> C) β<sub>1</sub> D) β<sub>4 </sub>+ β<sub>5</sub> Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model:
TABLE 14-11 A weight-loss clinic wants to use regression analysis to build a model for weight-loss of a client (measured in pounds) . Two variables thought to affect weight loss are client's length of time on the weight loss program and time of session. These variables are described below: Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model: Partial output from Microsoft Excel follows: Regression Statistics ANOVA -Referring to Table 14-11, in terms of the β's in the model, give the average change in weight-loss (Y) for every 1 month increase in time in the program (X<sub>1</sub>) when attending the evening session. A) β<sub>1 </sub>+ β<sub>4</sub> B) β<sub>1 </sub>+ β<sub>5</sub> C) β<sub>1</sub> D) β<sub>4 </sub>+ β<sub>5</sub> Partial output from Microsoft Excel follows:
Regression Statistics
TABLE 14-11 A weight-loss clinic wants to use regression analysis to build a model for weight-loss of a client (measured in pounds) . Two variables thought to affect weight loss are client's length of time on the weight loss program and time of session. These variables are described below: Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model: Partial output from Microsoft Excel follows: Regression Statistics ANOVA -Referring to Table 14-11, in terms of the β's in the model, give the average change in weight-loss (Y) for every 1 month increase in time in the program (X<sub>1</sub>) when attending the evening session. A) β<sub>1 </sub>+ β<sub>4</sub> B) β<sub>1 </sub>+ β<sub>5</sub> C) β<sub>1</sub> D) β<sub>4 </sub>+ β<sub>5</sub> ANOVA
TABLE 14-11 A weight-loss clinic wants to use regression analysis to build a model for weight-loss of a client (measured in pounds) . Two variables thought to affect weight loss are client's length of time on the weight loss program and time of session. These variables are described below: Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model: Partial output from Microsoft Excel follows: Regression Statistics ANOVA -Referring to Table 14-11, in terms of the β's in the model, give the average change in weight-loss (Y) for every 1 month increase in time in the program (X<sub>1</sub>) when attending the evening session. A) β<sub>1 </sub>+ β<sub>4</sub> B) β<sub>1 </sub>+ β<sub>5</sub> C) β<sub>1</sub> D) β<sub>4 </sub>+ β<sub>5</sub>
-Referring to Table 14-11, in terms of the β's in the model, give the average change in weight-loss (Y) for every 1 month increase in time in the program (X1) when attending the evening session.

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