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The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by Consumer Reports (Consumer Reports website). The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 24.7173 + 0.3028¤ , where a = price ($) and y = overall score. Brand Price ($) Score Bose 180 75 Scullcandy 150 72 Koss 95 61 Phillips/O'Neill 60 56 Denon 60 40 JVC 55 26 a. Compute SST, SSR, and SSE (to 3 decimals). SST = 1792 SSR = 1297.61: SSE = 494.386 b. Compute the coefficient of determination r (to 3 decimals). p2 = .724 Comment on the goodness of fit. Hint: If r? is greater than 0.70, the estimated regression equation provides a good fit. The least squares line provided a good fit as a large proportion of the variability in y has been explained by the least squares line c. What is the value of the sample correlation coefficient (to 3 decimals)? rxy = .366

The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by Consumer Reports (Consumer Reports website). The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 24.7173 + 0.3028¤ , where a = price ($) and y = overall score. Brand Price ($) Score Bose 180 75 Scullcandy 150 72 Koss 95 61 Phillips/O'Neill 60 56 Denon 60 40 JVC 55 26 a. Compute SST, SSR, and SSE (to 3 decimals). SST = 1792 SSR = 1297.61: SSE = 494.386 b. Compute the coefficient of determination r (to 3 decimals). p2 = .724 Comment on the goodness of fit. Hint: If r? is greater than 0.70, the estimated regression equation provides a good fit. The least squares line provided a good fit as a large proportion of the variability in y has been explained by the least squares line c. What is the value of the sample correlation coefficient (to 3 decimals)? rxy = .366

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
Problem 1P
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I need help just figuring out what part of the excel sheet tells me the answer for Rxy so i can be sure I know what to do. I know the rest of it! Thanks!

The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by Consumer Reports (Consumer Reports website). The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 24.7173 + 0.3028x , where x = price ($) and y = overall score. Brand Price ($) Score Bose 180 75 Scullcandy 150 72 Koss 95 61 Phillips/O'Neill 60 56 Denon 60 40 JVC 55 26 a. Compute SST, SSR, and SSE (to 3 decimals). SST = 1792 SSR = 1297.61: SSE = 494.386 b. Compute the coefficient of determination r2 (to 3 decimals). p2 = .724 Comment on the goodness of fit. Hint: If r2 is greater than 0.70, the estimated regression equation provides a good fit. The least squares line provided a good fit as a large proportion of the variability in y has been explained by the least squares line. c. What is the value of the sample correlation coefficient (to 3 decimals)? Txy .366
Transcribed Image Text:The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by Consumer Reports (Consumer Reports website). The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 24.7173 + 0.3028x , where x = price ($) and y = overall score. Brand Price ($) Score Bose 180 75 Scullcandy 150 72 Koss 95 61 Phillips/O'Neill 60 56 Denon 60 40 JVC 55 26 a. Compute SST, SSR, and SSE (to 3 decimals). SST = 1792 SSR = 1297.61: SSE = 494.386 b. Compute the coefficient of determination r2 (to 3 decimals). p2 = .724 Comment on the goodness of fit. Hint: If r2 is greater than 0.70, the estimated regression equation provides a good fit. The least squares line provided a good fit as a large proportion of the variability in y has been explained by the least squares line. c. What is the value of the sample correlation coefficient (to 3 decimals)? Txy .366
SUMMARY OUTPUT Regression Statistics Multiple R 0.811731 R Square 0.658907 Adjusted R 0.545209 Standard E 12.21357 Observatic 5 ANOVA df SS MS ignificance F Regressior 1 864.4861 864.4861 5.795257 0.095245 Residual 3 447.5139 149.1713 Total 4 1312 Coefficientsandard Erre t Stat P-value Lower 95%Upper 95%ower 95.0%pper 95.0% Intercept 20.29521 13.87502 1.462715 0.239727 -23.8613 64.45173 -23.8613 64.45173 180 0.365533 0.151842 2.407334 0.095245 -0.11769 0.848761 -0.11769 0.848761
Transcribed Image Text:SUMMARY OUTPUT Regression Statistics Multiple R 0.811731 R Square 0.658907 Adjusted R 0.545209 Standard E 12.21357 Observatic 5 ANOVA df SS MS ignificance F Regressior 1 864.4861 864.4861 5.795257 0.095245 Residual 3 447.5139 149.1713 Total 4 1312 Coefficientsandard Erre t Stat P-value Lower 95%Upper 95%ower 95.0%pper 95.0% Intercept 20.29521 13.87502 1.462715 0.239727 -23.8613 64.45173 -23.8613 64.45173 180 0.365533 0.151842 2.407334 0.095245 -0.11769 0.848761 -0.11769 0.848761
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