Numbers d and e only The image consists of a scatterplot and a table displaying statistical data for 30 baseball teams in 2017. The number of wins (horizontal axis) is compared against attendance per game (vertical axis). A least-squares regression line is depicted, showing a positive correlation.**Scatterplot:**- **Y-Axis:** Attendance per Game (from 15,000 to 50,000).- **X-Axis:** Number of Wins (from 60 to 110).- The line represents the least-squares regression.**Table:**- Provides coefficients, standard errors, T-Values, and P-Values for the regression model.- **Term:** Constant (Coefficients: 10834, SE Coef: 9716, T-Value: 1.12, P-Value: 0.274) and Wins (Coefficients: 235, SE Coef: 119, T-Value: 1.98, P-Value: 0.058).- **Summary Statistics:** \( S = 7,377 \), \( R^2 = 12.29\% \), \( \text{Adj } R^2 = 9.16\% \).**Questions:**a) Using the information above, what is the equation of the least-squares regression line?b) What is the value of the correlation coefficient for the sample?c) Interpret the slope of the least-squares regression line in context.d) Explain why it is not reasonable to use the least-squares regression model to predict attendance per game for 0 wins.e) If the point representing 64 wins and an attendance of 40,786 people per game is removed from the set of data and a new regression analysis is conducted, how would the slope of the least-squares line be affected? Explain your reasoning.

Name: Numbers d and e only The image consists of a scatterplot and a table d
Uploaded: 2024-03-20T06:38:44.000Z
Channel: Bartleby
Description: Numbers d and e only The image consists of a scatterplot and a table displaying statistical data for 30 baseball teams in 2017. The number of wins (horizontal axis) is compared against attendance per game (vertical axis). A least-squares regression l