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: 1) client's length of time on the weight loss program; and 2) time of session, which is in the morning or the afternoon.
Variables:Y = weight loss (in pounds)X1 = Length of time in weight loss program (in months)X2 = 1 if morning session; 0 if afternoon session. Data for 25 clients on a weight loss program at the clinic were collected adn used to fit the interaction model : Y = B0 + B1X1 + B2X2 + B3X1X2 + E
The regression analysis is below:Regression Statistics Multiple R 0.7308 R Square 0.5341 Adjusted R Square 0.4675 Standard Error 43.3275 Observations 25 ANOVA df SS MS F Significance F Regression 3 45194.0661 15064.689 8.0248 0.0009 Residual 21 39422.6542 1877.2692 Total 24 84616.7203 Coefficients Standard Error t Stat P-Value Lower 99% Upper 99%Intercept -20.7298 22.371 -0.9266 0.3646 -84.0702 42.6106Length 7.2472 1.4992 4.834 0.0001 3.0024 11.4919Morn 90.1981 40.2336 2.2419 0.0359 -23.7176 204.1138Length x Morn -5.1024 3.3511 -1.5226 0.1428 -14.5905 4.3857
Questions:1) What is the experimental unit for this analysis (i. e. a "row" in the data set)?a. a clinicb. a client on a weight loss programc. a monthd. a morning, afternoon, or evening session2) Fill in the blanks for the regression equation for an afternoon session:Weight loss = + * Length of time(where weight loss is in pounds and length of time is in months)3) Fill in the blanks for the regression equation for a morning session:Weight loss = + * Length of time(where weight loss is in pounds and length of time is in months)