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The Management of a Professional Baseball Team Is in the Process

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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 = β\beta 0 + β\beta 1x1 + β\beta 2x2 + β\beta 3x3 + ε\varepsilon 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 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 = \beta <sub>0</sub> + \beta <sub>1</sub>x<sub>1</sub> + \beta <sub>2</sub>x<sub>2</sub> + \beta <sub>3</sub>x<sub>3</sub> + \varepsilon where: Y = attendance at a home game x<sub>1</sub> = current power rating of the team on a scale from 0 to 100 before the game. x<sub>2</sub> and x<sub>3</sub> are dummy variables,and they are defined below. x<sub>2</sub> = 1,if weekend x<sub>2</sub>= 0,otherwise x<sub>3</sub>= 1,if weather is favorable x<sub>3</sub>= 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: Interpret the estimated model coefficient b<sub>3</sub>. The multiple regression compute output also indicated the following: 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 = \beta <sub>0</sub> + \beta <sub>1</sub>x<sub>1</sub> + \beta <sub>2</sub>x<sub>2</sub> + \beta <sub>3</sub>x<sub>3</sub> + \varepsilon where: Y = attendance at a home game x<sub>1</sub> = current power rating of the team on a scale from 0 to 100 before the game. x<sub>2</sub> and x<sub>3</sub> are dummy variables,and they are defined below. x<sub>2</sub> = 1,if weekend x<sub>2</sub>= 0,otherwise x<sub>3</sub>= 1,if weather is favorable x<sub>3</sub>= 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: Interpret the estimated model coefficient b<sub>3</sub>. Interpret the estimated model coefficient b3.

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