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1 1341 chapter 01 an introduction to business

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Unformatted text preview: s 85 and predict the attendance for today's game. 1-1344 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. 1-1345 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? 1-1346 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? 1-1347 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. 1-1348 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. 1-1349 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. 1-1350 = .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 1-1351 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? 1-1352 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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This document was uploaded on 01/20/2014.

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