In: Statistics and Probability
The following table lists a portion of Major League Baseball’s (MLB’s) leading pitchers, each pitcher’s salary (In $ millions), and earned run average (ERA) for 2008.
Salary | ERA | |
J. Santana | 10.0 | 2.49 |
C. Lee | 4.0 | 2.30 |
T. Lincecum | 0.1 | 2.38 |
C. Sabathia | 8.0 | 2.07 |
R. Halladay | 7.0 | 2.47 |
J. Peavy | 6.2 | 2.80 |
D. Matsuzaka | 7.0 | 2.28 |
R. Dempster | 6.2 | 2.52 |
B. Sheets | 10.7 | 2.69 |
C. Hamels | 0.5 | 2.75 |
a-1. Estimate the model: Salary = β0 + β1ERA + ε. (Negative values should be indicated by a minus sign. Enter your answers, in millions, rounded to 2 decimal places.)
Salaryˆ=Salary^= + ERA
a-2. Interpret the coefficient of ERA.
A one-unit increase in ERA, predicted salary decreases by $0.99 million.
A one-unit increase in ERA, predicted salary increases by $0.99 million.
A one-unit increase in ERA, predicted salary decreases by $7.43 million.
A one-unit increase in ERA, predicted salary increases by $7.43 million.
b. Use the estimated model to predict salary for each player, given his ERA. For example, use the sample regression equation to predict the salary for J. Santana with ERA = 2.49. (Round coefficient estimates to at least 4 decimal places and final answers, in millions, to 2 decimal places.)
c. Derive the corresponding residuals. (Negative values should be indicated by a minus sign. Round coefficient estimates to at least 4 decimal places and final answers, in millions, to 2 decimal places.)