For major league baseball teams, do higher player payrolls mean more gate money? Here are data for each of the American League teams in the year 2002, The variable x denotes the player payroll (in millins of dollars) for the year 2002, and the variable y denotes the mean attendance (in thousands of fans) for the 81 home games that year. The data are plotted in the scatter plot below, as is the least-squares regression line. The equation for this line is y = 11.43 + 0.23x. Player payroll, Мean attendance, y x (in $1,000,000s) thousands) (in Anaheim Baltimore Boston Chicago White Sox Cleveland 62.8 28.52 56.5 33.09 110.2 32.72 54.5 20.74 74.9 32.35 Detroit 54.4 18.52 Kansas City 49.4 16.30 Minnesota New York Yankees Oakland 41.3 23.70 133.4 42.84 41.9 26.79 Seattle Tampa Bay 86.1 43.70 Player payroll, x (in $1,000,000s) 34.7 13.21 Техas 106.9 29.01 Toronto 66.8 20.25 Send data to calculator v Send data to Excel Based on the sample data and the regression line, complete the following. (a) For these data, mean attendance values that are greater than the mean of the mean attendance values tend to be paired with player payroll values that are (Choose one) | the mean of the player payroll values. ? (b) According to the regression equation, for an increase of one million dollars in player payroll, there is a corresponding increase of how many thousand fans in mean attendance? (c) From the regression equation, what is the predicted mean attendance (in thousands of fans) when the player payroll is 54.4 million dollars? (Round your answer to at least two decimal places.) |(d) From the regression equation, what is the predicted mean attendance (in thousands of fans) when the player payroll is 121.0 million dollars? (Round your answer to at least two decimal places.) Mean attendance, y (spuesnou ui)
For major league baseball teams, do higher player payrolls mean more gate money? Here are data for each of the American League teams in the year 2002, The variable x denotes the player payroll (in millins of dollars) for the year 2002, and the variable y denotes the mean attendance (in thousands of fans) for the 81 home games that year. The data are plotted in the scatter plot below, as is the least-squares regression line. The equation for this line is y = 11.43 + 0.23x. Player payroll, Мean attendance, y x (in $1,000,000s) thousands) (in Anaheim Baltimore Boston Chicago White Sox Cleveland 62.8 28.52 56.5 33.09 110.2 32.72 54.5 20.74 74.9 32.35 Detroit 54.4 18.52 Kansas City 49.4 16.30 Minnesota New York Yankees Oakland 41.3 23.70 133.4 42.84 41.9 26.79 Seattle Tampa Bay 86.1 43.70 Player payroll, x (in $1,000,000s) 34.7 13.21 Техas 106.9 29.01 Toronto 66.8 20.25 Send data to calculator v Send data to Excel Based on the sample data and the regression line, complete the following. (a) For these data, mean attendance values that are greater than the mean of the mean attendance values tend to be paired with player payroll values that are (Choose one) | the mean of the player payroll values. ? (b) According to the regression equation, for an increase of one million dollars in player payroll, there is a corresponding increase of how many thousand fans in mean attendance? (c) From the regression equation, what is the predicted mean attendance (in thousands of fans) when the player payroll is 54.4 million dollars? (Round your answer to at least two decimal places.) |(d) From the regression equation, what is the predicted mean attendance (in thousands of fans) when the player payroll is 121.0 million dollars? (Round your answer to at least two decimal places.) Mean attendance, y (spuesnou ui)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:For major league baseball teams, do higher player payrolls mean more gate money? Here are data for each of the American League teams in the year 2002. The
variable x denotes the player payroll (in millions of dollars) for the year 2002, and the variable y denotes the mean attendance (in thousands of fans) for the 81
home games that year. The data are plotted in the scatter plot below, as is the least-squares regression line. The equation for this line is y = 11.43 + 0.23x.
Player
payroll,
x (in
Mean
attendance, y
(in
$1,000,000s) thousands)
Anaheim
62.8
28.52
Baltimore
56.5
33.09
40-
Boston
110.2
32.72
35
Chicago White
Sox
54.5
20.74
30-
Cleveland
74.9
32.35
25-
Detroit
54.4
18.52
Kansas City
49.4
16.30
15-
Minnesota
41.3
23.70
10+
New York
Yankees
133.4
42.84
Oakland
41.9
26.79
20
40
60
80
100
120
140
Seattle
86.1
43.70
Player payroll,
Тarmpa Bay
34.7
13.21
X (in
$1,000,000s)
Техas
106.9
29.01
Toronto
66.8
20.25
Send data to calculator
Send data to Excel
Based on the sample data and the regression line, complete the following.
(a) For these data, mean attendance values that are greater than the mean of the mean attendance values tend to be paired
with player payroll values that are (Choose one)
|the mean of the player payroll values.
?
(b) According to the regression equation, for an increase of one million dollars in player payroll, there is a corresponding
increase of how many thousand fans in mean attendance?
(c) From the regression equation, what is the predicted mean attendance (in thousands of fans) when the player payroll is
54.4 million dollars? (Round your answer to at least two decimal places.)
(d) From the regression equation, what is the predicted mean attendance (in thousands of fans) when the player payroll is
121.0 million dollars? (Round your answer to at least two decimal places.)
Mean attendance, y
(in thousands)
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