Ten observations were provided for a dependent variable y and two independent variables X1 and X2; for these data, SST = 15,186.1 and SSR = 14,0651. (3) Compute R2. (Round your answer to three decimal places.) R2=_, 2 . (b) Compute 112'a . (Round your answer to three decumal places.) 2_ . R. _x (c) Does the estimated regression equation explain a large amount of the variability in the data? Explain. (For purposes of this exercise, consider an amount large if it is at least 55%. Round your answer to one decimal place.) J , after adjusting for the number of independent variables in the model, we see that X % of the variability in y has been accounted for. weed W m m The owner of a movie theater company used multiple regression analysis to predict gross revenue 0/) as a function of television advertising (X1) and newspaper advertising (X2). The estimated regression equation was y = 83.5 + 2.23):1 + 1.20x2. The computer solution, based on a sample of eight weeks, provided SST = 25.3 and SSR = 23.395. (a) Compute and interpret R2 and R62. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is .925 / . Adjusting for the number of independent variables in the model, the proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is 0.915 x (b) When television advertising was the only independent variable, R2 = 0.653 and R62 = 0.595. Do you prefer the multiple regression results? Explain. Multiple regression analysis / preferred since both R2 and Ra2 show / percentage of the variability of y explained when both independent variables are used. '-leei:ll~s|::-""I Rndlt II 1.th DATAfile: ExerZ A statistical program is recommended. andx. Consider the following data for a dependent variable y and two independent variables, x1 2 x1 '2 Y 30 12 94 47 10 108 59 13 142 76 16 211 (a) Develop an estimated regression equation relating y to x1. (Round your numerical values to one decimal place.) f}: Predict y if x1 = 36. (Round your answer to one decimal place.) E (b) Develop an estimated regression equation relating y to x2. (Round your numerical values to one decimal place.) )7: Predict y if x2 = 12. (Round your answer to one decimal place.) E (c) Develop an estimated regression equation relating y to x and x2. (Round your numerical values to one decimal place.) 1 f}: Predict y if x1 = 36 and x2 = 12. (Round your answer to one decimal place.) E