1. The following scatterplot shows the number of wins and the attendance per game for 30 baseball teams in 2017. Also shown are the least-squares regression line and computer output. 50,000 45,000 er Game 40,000- Attendance per 35,000 30,000 25,000+ 20,000 15,000 60 70 80 90 100 Number of Wins Term Coel SE Coel T-Value P.Value Constant 10834 9716 1.12 0.274 Wins 235 119 1.98 0.058 S =7,377 R - 8q = 12.29% Adj R - sq = 9.16% (a) Interpret the slope of the least-squares regression line in context. (b) Explain why it is not reasonable to use the least-squares regression model to predict attendance per game for a team with 0 wins. (c) What is the value of the correlation coefficient for the sample? (d) If the point representing 64 wins and attendance of 40,786 people per game is removed from the set of data and a new regression analysis is conducted, how would the following be impacted? Explain your reasoning. (i) The slope of the least-squares line: (ii) The correlation coefficient