Unformatted text preview: tive: 7
Topic: Dummy variables 11420 Chapter 01  An Introduction to Business Statistics 95. The management of a professional baseball team is in the process of determining the
budget for next year. A major component of future revenue is attendance at the home games.
In order to predict attendance at home games the team statistician has used a multiple
regression model with dummy variables. The model is of the form: y = β0 + β1x1 + β2x2 +
β3x3 + ε where:
Y = attendance at a home game
x1 = current power rating of the team on a scale from 0 to 100 before the game.
x2 and x3 are dummy variables, and they are defined below.
x2 = 1, if weekend
x2= 0, otherwise
x3= 1, if weather is favorable
x3= 0, otherwise
After collecting the data based on 30 games from last year, and implementing the above stated
multiple regression model, the team statistician obtained the following least squares multiple
regression equation:
The multiple regression compute output also indicated the following:
Assume that the overall model is useful in predicting the game attendance and the team
statistician wants to know if the mean attendance is higher on the weekends as compared to
the weekdays. At α = .05, test to determine if the attendance is higher on weekend home
games.
Reject H0. Attendance on weekend games is higher. AACSB: Analytic
Bloom's: Application
Difficulty: Hard
Learning Objective: 7
Topic: Dummy variables 11421 Chapter 01  An Introduction to Business Statistics 96. The management of a professional baseball team is in the process of determining the
budget for next year. A major component of future revenue is attendance at the home games.
In order to predict attendance at home games the team statistician has used a multiple
regression model with dummy variables. The model is of the form: y = β0 + β1x1 + β2x2 +
β3x3 + ε where:
Y = attendance at a home game
x1 = current power rating of the team on a scale from 0 to 100 before the game.
x2 and x3 are dummy variables, and they are defined below.
x2 = 1, if weekend
x2= 0, otherwise
x3= 1, if weather is favorable
x3= 0, otherwise
After collecting the data based on 30 games from last year, and implementing the above stated
multiple regression model, the team statistician obtained the following least squares multiple
regression equation:
The multiple regression compute output also indicated the following:
Assume that the overall model is useful in predicting the game attendance. Assume today is
Wednesday morning and the weather forecast indicates sunny, excellent weather conditions
for the rest of the day. Later today, there is a home baseball game for this team. Assume that
the current power rating of the team is 85 and predict the attendance for today's game.
25,600 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 7
Topic: Multiple regression model 11422 Chapter 01  An Introduction to Business Statistics 97. The management of a professional baseball team is in the process of determining the
budget for next year. A major component of future revenue is attendance at the home games.
In order to predict attendance at home games the team statistician has used a multiple
regression model with dummy variables. The model is of the form: y = β0 + β1x1 + β2x2 +
β3x3 + ε where:
Y = attendance at a home game
x1 = current power rating of the team on a scale from 0 to 100 before the game.
x2 and x3 are dummy variables, and they are defined below.
x2 = 1, if weekend
x2= 0, otherwise
x3= 1, if weather is favorable
x3= 0, otherwise
After collecting the data based on 30 games from last year, and implementing the above stated
multiple regression model, the team statistician obtained the following least squares multiple
regression equation:
The multiple regression compute output also indicated the following:
Assume today is Saturday morning and the weather forecast indicates sunny, excellent
weather conditions for the rest of the day and that the overall model is useful in predicting the
game attendance. Later today, there is a home baseball game for this team. If the current
power rating of the team is 92, use the model given above and predict the attendance for
today's game.
29,550 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 7
Topic: Multiple regression model 11423 Chapter 01  An Introduction to Business Statistics 98. A multiple regression model with four independent variables consists of 29 observations.
Multiple coefficient of determination, R2 = .80 and the standard error, s = 2.0. Complete the
analysis of variance table for this model and test the overall model for significance.
F = 24, reject H0. The model is significant. Since 24 > 2.78, reject H0. AACSB: Analytic
Bloom's: Application
Difficulty: Hard
Learning Objective: 4
Topic: Overall F test 11424 Chapter 01  An Introduction to Business Statistics 99. A multiple regression model with 3 independent variables and 16 observations produced
the following results: SSE = 15 and R2 = 2/3. Complete the analysis of variance table and
calculate the F statistic.
F = 8.0 AACSB: Analytic
Bloom's: Application
Difficulty: Hard
Learning Objective: 4
Topic: Overall F test 11...
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