The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is  ŷ = 21.258 + 0.327x,  where x = price ($) and y = overall score. Brand Price ($) Score A 180 74 B 150 73 C 95 59 D 70 54 E 70 40 F 35 24

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The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is 
ŷ = 21.258 + 0.327x,
 where x = price ($) and y = overall score.
Brand Price ($) Score
A 180 74
B 150 73
C 95 59
D 70 54
E 70 40
F 35 24
(a)
Compute SST, SSR, and SSE. (Round your answers to three decimal places.)
SST= SSR= SSE= 
(b)
Compute the coefficient of determination 
r2.
 (Round your answer to three decimal places.)
r2
 =  
Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.)
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.The least squares line did not provide a good fit as a large proportion of the variability in y has been explained by the least squares line.    The least squares line did not provide a good fit as a small proportion of the variability in y has been explained by the least squares line.The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line.
(c)
What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)
 
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