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A regression model relating y, the annual sales (in thousands of dollars) at a b

ID: 1099022 • Letter: A

Question

A regression model relating y, the annual sales (in thousands of dollars) at a branch office to x, number of salespersons at the office, provided the following regression summary output.









The exercise involves filling in the values for the numbered cells in yellow.













SUMMARY OUTPUT







Regression Statistics






Multiple R








R Square
(5)






Adjusted R Square







Standard Error (4)






Observations (3)
















ANOVA



df SS MS F Significance F



Regression 1 (2)
61.666 1.38E-05



Residual 28 (1) 82.1





Total 29 9127.4






Coefficients Std Error t Stat P-value Lower 95% Upper 95%


Intercept 80.246 11.333 7.081 1.06E-07 57.031 103.461


PERSONS 50.386 (6) (7) 5.99E-10 (8) (9)





















11 How many branch offices were involved in the study?



a 29







b 30







c 31







d 32

















12 The predicted annual sales at an office with 12 salespersons is $______ thousand.

a $714.88







b $704.88







c $694.88







d $684.88

















13 The value for SSE in (1) is:





a 2198.8







b 2298.8







c 2398.8







d 2498.8

















14 The variance of the prediction error is ______




a 2298.8







b 47.95







c 82.1







d 9.06

















15 The value for SSR in (2) is:





a 6828.6







b 6928.6







c 7028.6







d 7128.6

















16 The value for the standard error of estimate se(e) in (4) is:


a 9.303







b 9.061







c 8.819







d 8.577

















17 The value for R A regression model relating y, the annual sales (in thousands of dollars) at a branch office to x, number of salespersons at the office, provided the following regression summary output.









The exercise involves filling in the values for the numbered cells in yellow.













SUMMARY OUTPUT







Regression Statistics






Multiple R








R Square
(5)






Adjusted R Square







Standard Error (4)






Observations (3)
















ANOVA



df SS MS F Significance F



Regression 1 (2)
61.666 1.38E-05



Residual 28 (1) 82.1





Total 29 9127.4






Coefficients Std Error t Stat P-value Lower 95% Upper 95%


Intercept 80.246 11.333 7.081 1.06E-07 57.031 103.461


PERSONS 50.386 (6) (7) 5.99E-10 (8) (9)





















11 How many branch offices were involved in the study?



a 29







b 30







c 31







d 32

















12 The predicted annual sales at an office with 12 salespersons is $______ thousand.

a $714.88







b $704.88







c $694.88







d $684.88

















13 The value for SSE in (1) is:





a 2198.8







b 2298.8







c 2398.8







d 2498.8

















14 The variance of the prediction error is ______




a 2298.8







b 47.95







c 82.1







d 9.06

















15 The value for SSR in (2) is:





a 6828.6







b 6928.6







c 7028.6







d 7128.6

















16 The value for the standard error of estimate se(e) in (4) is:


a 9.303







b 9.061







c 8.819







d 8.577

















17 The value for R

Explanation / Answer

11. Number of branch offices were involved in the study = 30 (b)

12. predicted annual sales at an office with 12 salespersons is $684.88 thousand (d)

13. The value for SSE in (1) is =2298.8    (b)

14. variance of the prediction error is= 82.1 (c)

15. value for SSR in (2) is= 6828.6   (a)

16. value for the standard error of estimate se(e) in (4) is= 9.061 (b)

17.The value for R

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