e 0 webassign nei \"www.mww \"3...... so .. my; PM\". .;.. .. O The estimated regression equation did not provide a good t as a large proportion of the variability in y has been explained by the estimated regression equation 0 111a estimated regression equation providEd a good t as a small proportion of the variability In y has been explained by the estimated regression equation. C The estimated regression equation did not provide a good t as a small proportion of the variability In y has been explained by the estimated regression equation ASWSBE14 15.E.015. ASKYOURTEACHER V The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (x2).The estimate} regression equation was f/ = 82.1 + 2.21X1 + 1.6Ox2. The computer solution, based on a sample of eight weeks, provided SST = 25.8 and SSR = 23.445. (3) Compute and interpret R2 and R32. (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 . 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 (b) When television adVeI'tising was the only independent variable, R2 = 0.653 and RE2 : 0.595. Do you prefer the multiple regression results? Explain. Multiple regression analysis ---Se|eci-- preferred since both R2 and Ra2 show --vSelect--- percentage of the variability of y explained when both independent variables are used. 10. [-l10 Points] ASWSBE1415.E.017. PSKYOURTEACHEK' ' i A statistical program is recommended. ' Kentuc Spring is a peak time for selling houses. Suppose the data below contains the selling price, number of bathrooms, square footage, and number of bedrooms of 26 homes sold in FLTnomas. kit. in spring 2018. Selling Price Baths Sq Ft Beds 160,000 . 295,000 2.5 1,860 3