Chapter 13 Simple Linear Regression 1. The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The following data represents the value in 2014 (in $millions) and the annual revenue (in $millions) for the 30 Major League Baseball franchises. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated. Team Revenue 245 370 227 Value 1000 2100 975 825 207 254 175 231 304 1125 800 700 1300 223 508 202 250 895 3200 725 1100 625 188 266 1220 226 870 211 840 Baltimore Boston Chicago White Sox Cleveland Detroit Houston Kansas City Los Angeles Angels Minnesota New York Yankees Oakland Seattle Tampa Bay Texas Toronto Arizona Atlanta Chicago Cubs Cincinnati Colorado Los Angeles Dodgers Miami Milwaukee New York Mets Philadelphia Pittsburgh St. Louis San Diego San Francisco Washington 267 1150 1800 302 885 227 214 855 403 2400 188 650 226 875 1350 263 265 229 294 225 1250 900 1400 890 2000 1280 387 287 Multiple data on per Hint: Copy and paste the data to Excel, on the Data tab, click Data Analysis and select Regression. a. Construct a scatter plot in Excel. b. Write the simple linear regression equation and interpret the meaning of b. and b, in this problem. c. Determine the coefficient of determination, r2, and interpret its meaning. d. At the 0.05 level of significance, is there evidence of a linear relationship between annual revenue and franchise value? e. What is the 95% confidence interval for the mean value of a baseball franchise that generates $250 million of annual revenue? f. What is the 95% prediction interval for a baseball franchise that generat a $250 million of annual revenue