Larry Marks, the plant manager at Super Retailers is attempting to identify the variables that effect weekly sales of a relatively new detergent at his store. Correctly identifying the variables is important to ensure that money is spent in the right channels to boost sales and also for managing costs within the store. After considerable effort and elimination of a number of variables, Larry has identified the dollar amount spent on advertising and the square feet of shelf space allocated to this new product as two potential variables that effect future sales of this detergent. After identifying these variables, Larry has collected data (as shown in the table below) for the past 20 weeks. Larry is not sure about how to proceed from this point. He wants to know if these variables are good estimators of future sales. He has now approached you, the controller, with the following questions.

Based on the above data and using regression analysis, determine and state the cost estimation model to predict sales. Attach a copy of the regression output.
State the R2 and the t - stat's. Describe what these numbers mean.
Use the model to forecast sales if Larry expects to spend $840 on advertising and allocate 65 square feet of shelf space to this new product in the 21st week.

Transcribed Image Text:

Sales ($) Advertising ($) Shelf Space (ft2) Week 2,010 201 75 1,850 205 50 2,400 355 75 4 1,575 208 30 590 3,550 75 2,015 397 50 3,908 820 75 1,870 400 30 4,877 997 75 10 2,190 515 30 996 11 5,005 75 12 2,500 625 50 3,005 50 13 860 14 3,480 1012 50 15 5,500 1135 75 16 1,995 635 30 17 2,390 837 30 18 4,390 1200 990 19 2785 30 2989 1205 30 20