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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
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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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)
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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