For each data set, specify and estimate multiple regression models for a linear specication and a (log-linear) specication of the demand function for the Whopper (WhopQ). Based on your own assessment of the results, choose the best model and data set to be the basis for your report. Be sure to explain the rationale for your choice in your report, but don't try to present estimates from all the models in your report. In the main body of your report, present the regression results for the model and data set you have chosen. Discuss the signs, magnitudes, and statistical signicance of the parameters you have estimated. Give particular attention to interpretation of estimated relationships between demand for the 'Whopper and the each of the three price variables. What do your results imply about the demand relationships among the 1Whopper, Chicken Sandwich, and Jr. JNhopper?r Current prices for the \"Whopper, Chicken Sandwich, and Jr. \"rhopper are: $2.19, $2.59, and $1.69 respectively. Calculate the price elasticity of demand for the Whopper with regard to its own price, the price of the Chicken Sandwich, and the price of the Jr. Whopper and explain ie implications of your elasticity estimates. Once again, current prices for the Whopper, Chicken Sandwich, and Jr. Whopper are: $2.19, $2.59, and $1.69 respectively. Two sets of promotional prices are being considered: i) $1.49, $2.59, and $0.99 for the Whopper, Chicken Sandwich, and Jr. Whopper, respectively ii) $0.99, $2.59, and $0.99 for the Whopper, Chicken Sandwich, and Jr. Whopper, respectively. Use your regression results to project daily demand for the Whopper under current prices and each of these price scenarios. If your boss points to maximize expected sales revenue from the 'Whopper, which set of prices should he choose