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We want a regression model to predict USGross. Parts of the regression output computed in Excel look like this: Dependent variable is: USGross($) = 47.4% R squared (adjusted) = 46.0% R squared 46.41 with 120 - 4 = 116 degrees of freedom For %3D S = Variable Coefficient SE(Coeff) t-ratio P-value - 25.70 -0.895 0.3729 Intercept Budget($) -22.9898 1.13442 0.1297 8.75 <0.0001 Stars 24.9724 5.884 4.24 <0.0001 Run Time -0.403296 0.2513 -1.60 0.1113 a) Write the multiple regression equation. b) What is the interpretation of the coefficient of Budget in this regression model? aldehsV

We want a regression model to predict USGross. Parts of the regression output computed in Excel look like this: Dependent variable is: USGross($) = 47.4% R squared (adjusted) = 46.0% R squared 46.41 with 120 - 4 = 116 degrees of freedom For %3D S = Variable Coefficient SE(Coeff) t-ratio P-value - 25.70 -0.895 0.3729 Intercept Budget($) -22.9898 1.13442 0.1297 8.75 <0.0001 Stars 24.9724 5.884 4.24 <0.0001 Run Time -0.403296 0.2513 -1.60 0.1113 a) Write the multiple regression equation. b) What is the interpretation of the coefficient of Budget in this regression model? aldehsV

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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U.S. Gross 3. 96 20 20 to this candy. (Be sure to include the units.) C) What does that residual say about her candy? Section 28.2 000 00 a 50 picture will make? We have data on a number of recent releases that includes the USGross (in $M), the Budget (SM), the Run Time (minutes), and the average number of Stars awarded by reviewers. The first several entries in the data table look like this: What (if anything) doe the following Assumpt regression? a) Linearity condition b) Equal Spread cond c) Normality assumpt Run Time Budget ($M) USGross Movie (minutes) Stars (W$) 56.094360 White Noise 101 2. 6. Movie residuals For togram of the residua Assumptions and Co Coach Carter 67.264877 45 136 3. Elektra 24.409722 65 2. Racing Stripes 49.772522 110 3. Assault on 20.040895 60 40 Precinct 13 Are We There 82.674398 94 2. Yet? Alone in the 5.178569 1.5 zeol -150 Dark 3.5 0s diw bosis Indigo 51.100486 25 We want a regression model to predict USGross. Parts of the regression output computed in Excel look like this: a) Linearity conditi b) Nearly Normal c c) Equal Spread co Dependent variable is: USGross($) R squared Section 28.4 47.4% R squared (adjusted) = 46.0% s = 46.41 with 120 – 4 = 116 degrees of freedom Tanimy emil el oldeis 7. Movie tests In the Exercise 3, %D %3D Del SE(Coeff) t-ratio P-value -R Variable Coefficient a) What is the null Stars in this tab Intercept -22.9898 25.70 -0.895 0.3729 Budget($) 1.13442 0.1297 8.75 b) What is the t-st c) What is the P-v d) Complete the b hypothesis? Stars 24.9724 5.884 4.24 Run Time -0.403296 0.2513 -1.60 0.1113 a) Write the multiple regression equation. b) What is the interpretation of the coefficient of Budget in this regression model? 8. More movie test a) What is the nu 4. Movie profits again A middle manager at an entertain- ment company, upon seeing the analysis of Exercise 3, concludes that longer movies make less money. He argues that his company's films should all be cut by 30 minutes to improve their gross. Explain the flaw in his interpretation of this model. 10 moioflooos Run Time in th b) What is the t-s c) Why is this t-s d) What is the P- do e) Complete the hypothesis?
Transcribed Image Text:U.S. Gross 3. 96 20 20 to this candy. (Be sure to include the units.) C) What does that residual say about her candy? Section 28.2 000 00 a 50 picture will make? We have data on a number of recent releases that includes the USGross (in $M), the Budget (SM), the Run Time (minutes), and the average number of Stars awarded by reviewers. The first several entries in the data table look like this: What (if anything) doe the following Assumpt regression? a) Linearity condition b) Equal Spread cond c) Normality assumpt Run Time Budget ($M) USGross Movie (minutes) Stars (W$) 56.094360 White Noise 101 2. 6. Movie residuals For togram of the residua Assumptions and Co Coach Carter 67.264877 45 136 3. Elektra 24.409722 65 2. Racing Stripes 49.772522 110 3. Assault on 20.040895 60 40 Precinct 13 Are We There 82.674398 94 2. Yet? Alone in the 5.178569 1.5 zeol -150 Dark 3.5 0s diw bosis Indigo 51.100486 25 We want a regression model to predict USGross. Parts of the regression output computed in Excel look like this: a) Linearity conditi b) Nearly Normal c c) Equal Spread co Dependent variable is: USGross($) R squared Section 28.4 47.4% R squared (adjusted) = 46.0% s = 46.41 with 120 – 4 = 116 degrees of freedom Tanimy emil el oldeis 7. Movie tests In the Exercise 3, %D %3D Del SE(Coeff) t-ratio P-value -R Variable Coefficient a) What is the null Stars in this tab Intercept -22.9898 25.70 -0.895 0.3729 Budget($) 1.13442 0.1297 8.75 b) What is the t-st c) What is the P-v d) Complete the b hypothesis? Stars 24.9724 5.884 4.24 Run Time -0.403296 0.2513 -1.60 0.1113 a) Write the multiple regression equation. b) What is the interpretation of the coefficient of Budget in this regression model? 8. More movie test a) What is the nu 4. Movie profits again A middle manager at an entertain- ment company, upon seeing the analysis of Exercise 3, concludes that longer movies make less money. He argues that his company's films should all be cut by 30 minutes to improve their gross. Explain the flaw in his interpretation of this model. 10 moioflooos Run Time in th b) What is the t-s c) Why is this t-s d) What is the P- do e) Complete the hypothesis?
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