Chapter 8, Problem 28E

(a)

To determine

To explain do you think a linear model is appropriate here.

Answer to Problem 28E

Yes, it is appropriate.

Explanation of Solution

In the question, it is given the scatterplot, residual plot and part of regression analysis of the relationship between the number of wins by American league baseball teams and the average attendance at their home games. The dependent variable is home attendance. And,

  $R^2=48.5\%$ .

Thus, we think a linear model is appropriate here because the line does seem to fit a majority of the data.

(b)

To determine

To interpret the meaning of $R^2$ in this context.

Explanation of Solution

In the question, it is given the scatterplot, residual plot and part of regression analysis of the relationship between the number of wins by American league baseball teams and the average attendance at their home games. The dependent variable is home attendance. And,

  $R^2=48.5\%$ .

In this context, the meaning of $R^2$ is that the linear model accurately predicts home attendance $48.5\%$ of the time.

(c)

To determine

To explain do the residual show any pattern worth remarking on.

Answer to Problem 28E

No, the residual does not show.

Explanation of Solution

In the question, it is given the scatterplot, residual plot and part of regression analysis of the relationship between the number of wins by American league baseball teams and the average attendance at their home games. The dependent variable is home attendance. And,

  $R^2=48.5\%$ .

Thus, we can say that the residual do not show any pattern worth remarking on because there is no real visible pattern shown in the residual plot.

(d)

To determine

To explain what can you say about the residual for the Yankees.

Answer to Problem 28E

The residual for Yankees is extremely high.

Explanation of Solution

In the question, it is given the scatterplot, residual plot and part of regression analysis of the relationship between the number of wins by American league baseball teams and the average attendance at their home games. The dependent variable is home attendance. And,

  $R^2=48.5\%$ .

Thus, we can say about the residual for the Yankees that the residual for the Yankees is extremely high because the actual value of home attendance for the Yankees is much higher than the value predicted by the linear model, the residual for the Yankees is high.