please do #30 In the previous chapter you looked at the relationship between the number of wins by American League baseball teams and the average attendance at their home games for the 2006 season. Here are the scatterplot, the residuals plot, and part of the regression analysis: Dependent variable is: Home Attendance R squared = 48.5% Variable Coefficient Constant - 14364.5 Wins 538.915 Do you think a linear model is appropriate here? Explain. Interpret the meaning of R2 in this context. Solution a) Linear model is not sufficent as the residuals against the predicted values are not distributed at random and they shows increasing tendency with predicted Y. Thsi may be due to the reason that the variance of the distubances term are not a constant, but increasing with increasing X b) R^2 =48.5% means that 48.5 % of variations in the home attendence are explained by the independece variable number of wins..

1. please do #30 In the previous chapter you looked at the relationship between the number of wins
by American League baseball teams and the average attendance at their home games for the
2006 season. Here are the scatterplot, the residuals plot, and part of the regression analysis:
Dependent variable is: Home Attendance R squared = 48.5% Variable Coefficient Constant -
14364.5 Wins 538.915 Do you think a linear model is appropriate here? Explain. Interpret the
meaning of R2 in this context.
Solution
a) Linear model is not sufficent as the residuals against the predicted values are not distributed at
random and they shows increasing tendency with predicted Y. Thsi may be due to the reason that
the variance of the distubances term are not a constant, but increasing with increasing X
b) R^2 =48.5% means that 48.5 % of variations in the home attendence are explained by the
independece variable number of wins.