50,000 1. 45,000- 40,000- 35,000 30,000 - 25,000- 20,000- 15,000- 60 70 80 90 100 Number of Wins Term Coef SE Coef T-Value P-Value Constant 10834 9716 1.12 0.274 Wins 235 119 1.98 0.058 S-7,377 R- sq = 12.29% Adj R - sq = 9.16% The scatterplot above 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. 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. Attendance per Game

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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50,000
1.
45,000-
40,000-
35,000-
30,000-
25,000-
20,000-
15,000 -
60
70
80
90
100
Number of Wins
Term
Coef
SE Coef
T-Value
P-Value
Constant
10834
9716
1.12
0.274
Wins
235
119
1.98
0.058
S = 7,377
R
sq = 12.29%
Adj R - sq
9.16%
The scatterplot above 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.
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 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.
Attendance per Game
Transcribed Image Text:50,000 1. 45,000- 40,000- 35,000- 30,000- 25,000- 20,000- 15,000 - 60 70 80 90 100 Number of Wins Term Coef SE Coef T-Value P-Value Constant 10834 9716 1.12 0.274 Wins 235 119 1.98 0.058 S = 7,377 R sq = 12.29% Adj R - sq 9.16% The scatterplot above 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. 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 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. Attendance per Game
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