Baseball team owners want to attract fans to games. The New York Mets acquired the pitcher Pedro Martinez in 2005. Martinez is considered one of the best pitchers of his era, having won the Cy
Young Award three times. Martinez had his own fans. Possibly, he attracted more fans to the ballpark when he pitched at home, helping to justify his four-year, $53 million contract. Is there really a
Pedro effect in attendance? A multiple regression from the data for a random selection of Mets home games is given. Complete parts (a) through (d) below.
Click to view the multiple regression output and list of predictors.
Multiple Regression Output
d) Could Pedro's agent claim, based on this regression, that his man attracts more fans to the ballpark?
Identify the hypotheses for the test.
A. H_(0):eta _(Pedro Start )!=0
H_(A):eta _(Pedro Start )=0
B. H_(0) : All of the eta coefficients are equal to 0 .
H_(A) : None of the eta coefficients are equal to 0 .
C. H_(0):eta _(Pedro Start )=0
H_(A):eta _(Pedro Start )!=0
D. H_(0) : All of the eta coefficients are equal to 0 .
H_(A) : At least one of the eta coefficients is not equal to 0 .
The test statistic is
(Type an integer or a decimal. Do not round.)
The regression has the following predictors:
Weekend ,1 if game is on Saturday or Sunday, 0 otherwise
Yankees 1 if game is against the Yankees (a hometown rivalry),
0 otherwise
Rain Delay ,1 if the game was delayed by rain (which might have
depressed attendance), 0 otherwise
Opening Day
1 for opening day, 0 for the others
Pedro Start 1 if Pedro was the starting pitcher, 0 otherwise
Dependent variable is: Attendance
R squared =66.6%
R squared (adjusted) =65.3%
s=6998 with 80-6=74 degrees of freedom
Baseball team owners want to attract fans to games. The New York Mets acquired the pitcher Pedro Martinez in 2005. Martinez is considered one of the best pitchers of his era, having won the Cy Young Award three times. Martinez had his own fans. Possibly, he attracted more fans to the ballpark when he pitched at home, helping to justify his four-year, $53 million contract. Is there really a Pedro effect in attendance? A multiple regression from the data for a random selection of Mets home games is given. Complete parts (a) through (d) below.
Click to view the multiple regression output and list of predictors.
Multiple Regression Output
The regression has the following predictors:
d) Could Pedro's agent claim, based on this regression, that his man attracts more fans to the ballpark?
Weekend Yankees
1 if game is on Saturday or Sunday, 0 otherwise 1 if game is against the Yankees (a hometown rivalry) 0 otherwise 1 if the game was delayed by rain (which might have depressed attendance),0 otherwise 1 for opening day,0 for the others 1 if Pedro was the starting pitcher, 0 otherwise
Identify the hypotheses for the test.
O A. Ho: PPedro Star # 0 HA: Pedro Start =0 B.Ho:All of the coefficients are equal to 0 H : None of the coefficients are equal to 0.
Rain Delay
Opening Day Pedro Start
Dependent variable is: Attendance R squared = 66.6% R squared (adjusted)=65.3% s = 6998 with 80 6 = 74 degrees of freedom
C c. Ho: Pedro Star=0 HA : PPedro Start # 0 D. Ho: All of the coefficients are equal to 0. HA : At least one of the coefficients is not equal to 0
Variable Intercept Weekend Yankees Rain Delay Opening Day Pedro Start
Coeff SE (Coeff) t-ratio P-value 27767 1373 20.23 <0.0001 9914 1203 8.24 <0.0001 15913 5413 2.94 0.0044 17216 8121 2.12 0.0374 25198 4278 5.89 <0.0001 5049 3581 1.41 0.1627
The test statistic is (Type an integer or a decimal. Do not round.)