Question

Exercise 15.41 Question 14 of 16 Check My Work eBook Video The following data describes weekly gross revenue, television advertising, and newspaper advertising for Showtime Movie Theaters. Weekly Gross Revenue ($1000s) Televison Advertising ($1000s) Newspaper Advertising ($1000s) 1.5 u w Ň w 2.5 a. Find an estimated regression equation relating weekly gross revenue to television advertising expenditures and newspaper advertising expenditures (to 2 decimals). TV Adv + 1.29 NewsAdv Revenue = 81.73 + 2.84 b. Select a standardized residuals plot. A. F N .

Answer 1

this is done in R software
rev <- c(95, 90, 95, 92, 95, 94, 94, 94) tel_ad < news_ad <- c(1.5, 2, 1.5, 2.5, 3.3, 2.3, 4.2, 2.5) с (5, 2, 4, 2.5, 3, 3.5, 2.5, 3) summary(1m(rev~tel_ad+news_ad)) #Call #1m(formula = rev ~ tel_ad news_ad) ## #Residuals: 2 8 ## 4 6 7 #0.9996 -0.6150 1.0129 -0.2741 0.6751 -0.0254 -0.4937 0.7197 Coefficients: Estimate Std. Error t value Pr(>|t|) 2.1060 39.876 1.87e- 07 *** #(Intercept) 83.9787 #tel_ad #news_ad ** 2.0125 0.4069 4.946 0.0043 1.3057 0.4291 3.043 0.0287 a* 0.001 #Signif. codes: 0.01 '*'0.05 .' 0.1'' 1 Residual standard error: 0.8598 on 5 degrees of freedom ##Multiple R-squared: 0.831, Adjusted R-squared: F-statistic: 12.29 on 2 and 5 DF, p-value: 0.01174 0.7634 As we can see the estimated fitted line is given by Revenue 83.9787 + 2.0125 Tv_ad + 1.3057 news_ad

rev <(95, 90, 95, 92, 95, 94, 94, 94) tel_ad < c(5, 2, 4, 2.5, 3, 3.5, 2.5, 3) news_ad - c(1.5, 2, 1.5, 2.5, 3.3, 2.3, 4.2, 2.5) 1m(rev tel_ad+news_ad) model plot(model) [1] Residuals vs Fitted TO 91 92 93 94 95 96 Fitted values Im(rev tel_ad news_ad) Residuals -1.0 -0.5 0.0 0.5 O

command for plot and equation is given above