Using regression analysis, the attached data and a linear functional form, estimate the demand and elasticity estimates for TRASCOTT BURGER . Include the computation and explanation of the following in your report: 1 . Write your regression equation i.e., demand function, enter information into excel as per instructions attached and compute the regression equation. (4pts) 2. Use the data provided to run your regression (10points) 3 . Using your regression output, write your estimated coefficients into the demand function. (5pts) 4. Interpret all the coefficients. (20pts) 5 . Using the average values for the independent variables and your estimated demand function, compute the demand for TRASCOTT in a typical market. (6pts 6. Define and interpret the standard error of the estimate AND estimate the range within which actual demand for TRASCOTT is expected to fall with a 95% confidence level. (10pts) 7 Define the coefficient of determination (R-squared). What percentage of demand variation is explained by this model? (5pts) 8. Are the coefficient's statistically significant? i.e., does each of the independent variable have a significant effect on the dependent variable? Explain using t-stats. (8pts) 9. Calculate and interpret the point price, cross price, point advertising and point income elasticity of demand for TRASCOTT Burgers. (12pts) 10. As a Business Analyst, use the elasticity analysis you have done to advise your manager on: The impact of an increase in the price of TRASCOTT on total revenues. Show your calculations. 15points b. The impact of rising incomes on the firm's total revenues. 5points Explain your answer, using your elasticity estimates including how much revenue would be generated (or lost) by an increase ( e.g., 1%, or $1 ) in price. For question 10 type a business memo to your manager, using your regression and elasticity results to support your recommendation. This is not a group project. Your final report must be typed. Please submit regression results (output) with your draft and final project and show your formulas and calculations.Calibri (Body) 12 B aA v General . . . V LAJ fx SUMMARY OUTPUT A B C D E F G H 28 29 SUMMARY OUTPUT 30 31 Regression Statistics 32 Multiple R 0.98626901 33 R Square 0.97272657 34 Adjusted R Sc 0.96698479 35 Standard Erro 33.609921 36 Observations 24 37 38 ANOVA 39 df SS MS F Significance F 40 Regression 4 765490.049 191372.512 169.412158 1.4121E-14 41 Residual 19 21462.909 1129.62679 42 Total 23 786952.958 43 44 Coefficients Standard Errol t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 45 Intercept 92.5483972 1331.41336 0.06951139 0.94530895 -2694.1318 2879.22859 -2694.1318 2879.22859 46 PRICE -83.929004 22.4872266 -3.7322968 0.00141185 -130.99531 -36.862697 -130.99531 -36.862697 47 INCOME 0.01824791 0.01908258 0.95625996 0.35095094 -0.0216924 0.05818821 -0.0216924 0.05818821 48 AD 288.033498 101.061254 2.8500883 0.01024028 76.509862 499.557133 76.509862 499.557133 49 PRICE BIG 51.1347989 68.6261958 0.7451207 0.46531686 -92.50148 194.771077 -92.50148 194.771077 50 51 52 Sheet1 + Sum :1769949.303