2. The file AnimatedMovieData.xlsx contains data from Box Office Mojo on animated movies. Key variables include the opening weekend gross revenue and lifetime gross revenue, both measured in U.S. dollars (you may ignore discount factors for this problem). Using this data, run a simple regression with lifetime gross revenue as the dependent variable and opening weekend gross revenue as the independent variable. Show a scatterplot of the data and your regression output. Explain your key findings, including specific interpretations of correlation, statistical significance, coefficient, etc. What other variables would you (ideally) like to include in a multiple regression if you aim to predict lifetime gross revenue? 3. The Hilton Hotel chain is developing a regression model to predict the operating margin of each of its franchises (operating margin is defined as the ratio of net profit to total revenue). Hilton plans to use this model to help identify profitable locations to build new hotels. You run a linear regression based on 100 hotels operated by Hilton, where the dependent variable is operating margin, and the independent variables are the number of hotel rooms within 1 mile of the hotel, and the amount of office space (in thousands of square feet) within 1 mile of the hotel. MANAGEMENT 402 DATA AND DECISIONS HOMEWORK 4 – REGRESSION AND DECISION ANALYSIS Dependent Variable: MARGIN Independent Variable: ROOMS, OFFICE Regression Statistics R R Square Adj.RSqr Std.Err. #Cases #Missing Deg.Free t(2.5%,97) 0.67 0.45 0.44 8.40 100 0 97 1.985 Summary Table Variable Coeff. Std.Err. t Stat P-value Lower95% Upper95% Intercept 53.983 5.178 10.425 0.000 43.705 64.261 ROOMS -0.0073 0.0013 -5.615 0.000 -0.010 -0.005 OFFICE 0.0216 0.0176 1.227 0.223 -0.013 0.057 (a) State the multiple regression prediction line equation. (b) Check whether each of the independent variables is significantly related to operating margin at ̑ = 0.05. (c) Two possible sites are being considered for a new hotel. Site A is near an office complex with 400 thousand square feet of office space, but there is a competing hotel chain within 1 mile that has 2,000 hotel rooms. Site B is more remote and has only 50 thousand square feet of office space nearby, but also less hotel competition with only 300 rooms nearby. Which hotel site has a higher predicted operating margin according to this regression?