Summary MGMT305 HW 5 In exercise 7 a sales manager collected the fol
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MGMT305HW#5Due date: April 17th, 20131. #19. In exercise 7 a sales manager collected the following data on x = annual sales and y = years of experience. The estimated regression equation for these data is (webfile: )a.Compute SST, SSR, and SSESST= SSR+SSEYearsSalesYbar80+4XSSTSSESSR-28784
20131 19 in exercise 7 a sales manager collected the following data on x annual sales and y years of experience the estimated regression equation for these data
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MGMT305
HW#5
Due date: April 17th, 2013
1. #19. In exercise 7 a sales manager collected the following data on x = annual sales and y =
years of experience. The estimated regression equation for these data is (webfile: sales.xls)
b. Compute the coefficient of determination r2. Comment on the goodness of fit.
R^2=SSR/SST=2272/2442=0.9304
We see that 93.04% of the variability in y has been explained by the least squares line.
c. What is the value of the sample correlation coefficient?
=(sign of b1) = =0.9645
2. # 20. Consumer Reports provided extensive testing and ratings for more than 100 HDTVs. An
overall score, based primarily on picture quality, was developed for each model. In general, a
, higher overall score indicates better performance. The following data show the price and overall
score for the ten 42-inch plasma televisions (Consumer Reports, March006). (Web file:
PlasmaTV.xls)
a. Use these data to develop an estimated regression equation that could be used to estimate the
overall score for a 42-inch plasma television given the price.
Chart Title
80
60
f(x) = 0.012696793002916 x + 12.0174927113703
Series2
40 R² = 0.450281217652254
Axis Title Linear (Series2)
20
0
1000 2000 3000 4000 5000
Axis Title
b. Compute r2. Did the estimated regression equation provide a good fit?
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