In 2016, the Los Angeles Dodgers spent nearly one quarter billion (!) dollars on salaries for their players (Spotrac). Is there a relationship between salary and team performance in Major League Baseball? For the 2016 season, a linear model fit to the number of Wins (out of 162 regular season games) from the team Salary ($M) for the 30 teams in the league is:

a) What is the explanatory variable?

b) What is the response variable?

c) What does the slope mean in this context?

d) What does the y-intercept mean in this context? Is it meaningful?

e) If one team spends $10 million more than another on salaries, how many more games on average would you predict them to win?

f) If a team spent $100 million on salaries and won half (81) of their games, would they have done better or worse than predicted?

g) What would the residual of the team in part f be?

h) The R² for this model is 38.6% and the residual standard deviation is 8.5 games. How useful is this model likely to be for predicting the number of wins?

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Wins = 63.81 + 0.136 Salary.