Unformatted text preview: s 85 and predict the attendance for today's game. 11344 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. 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. 11345 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. 100. Consider the following partial computer output for a multiple regression model. Analysis of Variance What is the total sum of squares? 11346 Chapter 01  An Introduction to Business Statistics 101. Consider the following partial computer output for a multiple regression model. Analysis of Variance What is the explained variation? 102. Consider the following partial computer output for a multiple regression model. Analysis of Variance What is the mean square error? 11347 Chapter 01  An Introduction to Business Statistics 103. Consider the following partial computer output for a multiple regression model. Analysis of Variance Calculate R2. 104. Consider the following partial computer output for a multiple regression model. Analysis of Variance Test the overall usefulness of the model at α = .01. Calculate F and make your decision. 11348 Chapter 01  An Introduction to Business Statistics 105. Consider the following partial computer output for a multiple regression model. Analysis of Variance What is the number of observations in the sample? 106. Consider the following partial computer output for a multiple regression model. Analysis of Variance Calculate the adjusted R2. 11349 Chapter 01  An Introduction to Business Statistics 107. Consider the following partial computer output for a multiple regression model. Analysis of Variance Write the least squares prediction equation. 108. Consider the following partial computer output for a multiple regression model. Analysis of Variance Test the usefulness of variable x2 in the model at
your conclusions. 11350 = .05. Calculate the t statistic and state Chapter 01  An Introduction to Business Statistics 109. Consider the following partial computer output for a multiple regression model. Analysis of Variance Determine the 95% interval for β2 and interpret its meaning 11351 Chapter 01  An Introduction to Business Statistics 110. A member of the state legislature has expressed concern about the differences in the
mathematics test scores of high school freshmen across the state. She asks her research
assistant to conduct a study to investigate what factors could account for the differences. The
research assistant looked at a random sample of school districts across the state and used the
factors of percentage of mathematics teachers in each district with a degree in mathematics,
the average age of mathematics teachers and the average salary of mathematics teachers s = 7.62090
Analysis of Variance What is the total sum of squares? 11352 Chapter 01  An Introduction to Business Statistics 111. A member of the state legislature has expressed concern about the differences in the
mathematics test scores of high school freshmen across the state. She asks her research
assistant to conduct a study to investigate what factors could account for the differences. The
research assistant looked at a random sample of school districts across the state and used the
factors of percentage of mathematics teachers in each district with a degree in mathematics,
the average age of mathematics teachers and the average salary of mathematics teachers s = 7.62090
Analysis of Var...
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 Winter '14
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