0000000000000000000000
Variable Mean Variable Mean SalesExp 7089.7 SalesCntl 6687.7 BPriceExp 1.213 BPriceCntl 1.218 CPriceExp 1.176 CPriceCntl 1.144 DUM 0.316 1) Run a regression of SalesExp against BPriceExp and CPriceExp. Provide the estimated regression equation. 2) Interpret the coefficients. 3) Is there evidence to conclude that an increase in the own price leads to a decrease in sales in the experimental group? 4) Is there evidence to conclude that the model for the experimental group is significant as a whole? Set up the appropriate hypotheses and conduct the test. 5) Run a regression of SalesExp against BPriceExp, CPriceExp and DUM. Provide the estimated regression equation. Interpret the coefficient of DUM in the experiment panel. What can you conclude about the effectiveness of the increased advertising strategy in the experiment panel based on these results? 6) Run a regression of SalesCntl against BPriceCntl, CPriceCntl and DUM. Provide the estimated regression equation. Interpret the coefficient of DUM in the control panel. Can you put the results from question 5 and 6 together to reach a conclusion about the effectiveness of the increased advertising in the experimental panel?2. The data in the file called \"Assign.xls" are from a eld experiment on a frequently purchased brand. We have available 76 weeks of data on a control panel of families and a matched experimental panel from the same town. Both panels are exposed to the same base level of advertising for the rst 52 weeks. For the last 24 weeks, the control panel is continued to be exposed to the base level while the experimental panel is exposed to twice the level of advertising as the control panel. The dependent variable is weekly sales of the brand undergoing the experiment. This is obtained by aggregating over all families who purchase the brand that week. The independent variables are own price and the chief competitive brand's price. A variable DUM was created which takes the value 0 for the rst 52 weeks and l forthe next 24 weeks. The variable DUM can be considered a PREIPOST variable, i.e., a variable that measures change in the last 24 weeks relative to the first 52 weeks. The variables in the le ASSIGN, in order from column 1 through column 8, are: Week, SalesExp (unit sales in experimental group), Saleantl (unit sales in control group), BPriceExp (brand's own price in experimental group), BpriceCntl (brand's own price in control group), CPriceExp (competitive brand's price in experimental group), CPriceCntl (competitive brand's price in control group), and DUM (defined above). To verify the accuracy of the data you have, you may compare the means of each variable in the data with the numbers below: Ecstatic Mme mum Mean SalesExp 7089.7 Saleantl 6687. 7 BPriceExp 1.213 BPriceCntl 1.2 l 8 CPriceExp l . l 76 CPriceCntl l . I44 DUM 0.316 1) Run a regression of SalesExp against BPriceExp and CPriceExp. Provide the estimated regression equation. 2) Interpret the coefcients. 3) Is there evidence to conclude that an increase in the own price leads to a decrease in sales in the experimental group? 4) Is there evidence to conclude that the model for the experimental group is signicant as a whole? Set up the appropriate hypotheses and conduct the test. 5) Run a regression of SalesExp against BPriceExp, CPriceExp and DUM. Provide the estimated regression equation. Interpret the coefficient of DUM in the experiment panel. What can you conclude about the effectiveness of the increased advertising strategy in the experiment panel based on these results
