A national chain of women's clothing stores with locations in the large shopping malls thinks that it can do a better job of planning more renovations and expansions if it understands what variables impact sales. It plans a small pilot study on stores in 25 different mall locations. The data it collects consist of monthly sales, store size (sq. ft), number of linear feet of window display, number of competitors located in mall, size of the mall (sq. ft), and distance to nearest competitor (ft). 1. Define a multiple regression model for the data. (6 marks) 2. Interpret the values of the coefficients in the model. (15 marks) 3. Test whether the model as a whole is significant. At the 0.05 level of significance, what is your conclusion? (2 marks) 4. Use the model to predict monthly sales for each of the stores in the study. (6 marks) 5. Find and interpret the value of 2 for this model. (2 marks) 6. Test the individual regression coefficients (i.e., check the result of test statistics that SAS or Excel provides). At the 0.05 level of significance, what are your conclusions? (2 marks) 7. If you were going to drop just one variable from the model, which one would you choose? Why? (2 marks)