A sports analyst for Major League Baseball wonders whether there is a relationship between a pitcher's salary (in $ millions) and his earned tun average (ERA). The accompanying table lists a portion of the data that she collected for 10 pitchers. Qcicktiere for the Excel Data File 0-1. Estimate the model: salary =0+1FAA+ (Negative volues should be indicated by a minus sign. Enter your onswers, in millions, rounded to 2 decimal places.) 0.2. Interpret the coefficient of ERA. A one-unit increase in ERA, predicted salary decreases by $2.26 miltion. A one-unit increase in ERA, predicted salary increases by $2.26 million. A one-unit increase in ERA, predicted salary decreases by $9.75 million. A one-unit increase in ERA, predicted salary increases by $9.75 million. b. Use the estimated model to predict salary for Player 1 and Player 2 . For example. use the sample regression equation to predict the salary for Pitcher 1 with ERA =228. (Do not round intermediate colculations. Round your finol answers (in millions) to 2 decimal ploces.) c. Derive the corresponding residuals for Player 1 and Player 2 (Negative values should be indicated by a minus sign. Round your final answers (in millions) to 2 decimal places.) A sports analyst for Major League Baseball wonders whether there is a relationship between a pitcher's salary (in $ millions) and his earned run average (ERA). The accompanying table lists a portion of the data that she collected for 10 pitchers. Qcickhere for the Excel Data File Q.1. Estimate the model: salary 0+1ERA+e. (Negative volues should be indicated by a minus sign. Enter your answers, in millions, rounded to 2 decimol ploces.) o-2. Interpret the coefficient of ERA A one-unit increase in ERA, predicted salary decreases by $226 million A one-unit increase in ERA, predicted salary increases by $2.26 million. A one-unit increase in ERA, predicted salary decreases by $975 million A one-unit increase in ERA, predicted salary increases by $975 million. b. Use the estimated model to predict salary for Player 1 and Player 2 . For example, use the sample regression equation to predict the salary for Pitcher 1 with ERA =2.28. (Do not round intermediote calculations. Round your final answers (in millions) to 2 decimal places.)