Is there a relationship between total team salary and the performance of footbal

Question

Is there a relationship between total team salary and the performance of football teams? For a season, a linear model predicting Wins (out of 16 regular season games) from the total team Salary ($M) is shown below. Complete parts a through h below. Wins = 5.096 + 0.023 salary a) What is the explanatory variable? A. Salary because the total salary is used to predict the number of wins B. Wins, because the total salary is used to predict the number of wins C. Salary because the number of wins is used to predict the total salary D. Wins, because the number of wins is used to predict the total salary b) What is the response variable? A. Wins, because the number of wins is determined from the total salary B. Salary because the total salary is determined from the number of wins C. Salary, because the number of wins is determined from the total salary D. Wins, because the total salary is determined from the number of wins c) What does the slope mean in this context? A. On average, teams who spend $5.096M more in salary win 0.023 fewer games B. On average, teams who spend $1M more in salary win 0.023 more games. C. On average, teams who spend $5.096M more in salary win 0.023 more games. D. On average, teams who spend $1M more in salary win 0.023 fewer games. d) What does the y-intercept mean in this context? Is it meaningful? A. 5.096 wins is a base value that is meaningful because the salary will be $0 B. $5.096M is a base value that is not meaningful because the wins will not be 0 games. C. 5.096 wins is a base value that is not meaningful because the salary will not be $0 D. $5.096M is a base value that is meaningful because the wins will be 0 games. e) If one team spends $9 million more than another on salary, how many more games on average would you predict them to win? On average, the team would be predicted to win more games. (Type an integer or a decimal) f) If a team spent $150 million on salaries and won 8 games, would they have done better or worse than predicted? The team would have done slightly than predicted. They are expected to win games. (Type an integer or a decimal) g) What would the residual of the team in part f be? The residual of the team would be games. (Type an integer or a decimal.) h) The residual standard deviation is 3 03games. What does this tell you about the likely practical use of this model for predicting wins? A. Not useful. The residual standard deviation says that we can not predict better than about +/-3 games. If 8 games are predicted, that's 5 to 11 games. B. Not useful. The residual standard deviation says that we can not predict better than about +/-6 games. If 8 games are predicted, that's 2 to 14 games. C. Useful. The low residual standard deviation shows that the model is a perfect fit for the data. D. Useful. The high residual standard deviation value shows that the model is a perfect fit for the data.

Explanation / Answer

Answer:

a).

A. salary is used to predict the number of wins.

b).

A. wins because the number of wins is determined from the total salary.

c).

B. on average teams spend $1M more in salary win 0.023 more games.

d).

C. 5.096 wins is a base value that is not meaningful because the salary will not be 0.

e). (9*0.023=0.207)

0.207

f).

predicted =5.096+0.023*150=8.546

less than predicted. They are expected to win 8.546 games.

g).

residual =8-8.546 = -0.546

h).

C. useful. The low residual sd shows the model is perfect fit for the data.

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