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TABLE 17-6 A Weight-Loss Clinic Wants to Use Regression Analysis to Build

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TABLE 17-6
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:
Y = Weight loss (in pounds)
X1 = Length of time in weight-loss program (in months)
X2 = 1 if morning session,0 if not
X3 = 1 if afternoon session,0 if not (Base level = evening session)
Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model:
Y = β0 + β1X1 + β2X2 + β3X3 + β4X1X2 + β5X1X3 + ε
Partial output from Microsoft Excel follows:
Regression Statistics TABLE 17-6 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: Y = Weight loss (in pounds)  X<sub>1 </sub>= Length of time in weight-loss program (in months)  X<sub>2</sub> = 1 if morning session,0 if not X<sub>3</sub> = 1 if afternoon session,0 if not (Base level = evening session)  Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + β<sub>4</sub>X<sub>1</sub>X<sub>2</sub> + β<sub>5</sub>X<sub>1</sub>X<sub>3</sub> + ε Partial output from Microsoft Excel follows: Regression Statistics   ANOVA F = 5.41118 Significance F = 0.040201   -Referring to Table 17-6,in terms of the βs in the model,give the mean change in weight loss (Y) for every 1-month increase in time in the program (X<sub>1</sub>) when attending the morning 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
F = 5.41118 Significance F = 0.040201 TABLE 17-6 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: Y = Weight loss (in pounds)  X<sub>1 </sub>= Length of time in weight-loss program (in months)  X<sub>2</sub> = 1 if morning session,0 if not X<sub>3</sub> = 1 if afternoon session,0 if not (Base level = evening session)  Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + β<sub>4</sub>X<sub>1</sub>X<sub>2</sub> + β<sub>5</sub>X<sub>1</sub>X<sub>3</sub> + ε Partial output from Microsoft Excel follows: Regression Statistics   ANOVA F = 5.41118 Significance F = 0.040201   -Referring to Table 17-6,in terms of the βs in the model,give the mean change in weight loss (Y) for every 1-month increase in time in the program (X<sub>1</sub>) when attending the morning 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 17-6,in terms of the βs in the model,give the mean change in weight loss (Y) for every 1-month increase in time in the program (X1) when attending the morning session.


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