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III. The I-10 Carpet Outlet wants to develop a means to forecast its sales. The

ID: 403364 • Letter: I

Question

III.   The I-10 Carpet Outlet wants to develop a means to forecast its sales. The store manager believes that the store%u2019s sales are directly related to the number of new housing starts in town. The manager has collected the following for the past 10 months:

Month     Monthly Carpet    Monthly Const.

                    Sales(1000s yd)      Permits

1                       5                           17

2                      12                          30

3                       6                           12

4                       5                           14

5                       8                           18

6                       4                           10

7                     14                           38

8                      9                            20

9                      9                            16

10                  16                            31























Compute the regression equation.?

Month     Monthly Carpet    Monthly Const.

                    Sales(1000s yd)      Permits

1                       5                           17

2                      12                          30

3                       6                           12

4                       5                           14

5                       8                           18

6                       4                           10

7                     14                           38

8                      9                            20

9                      9                            16

10                  16                            31

Explanation / Answer

FROM THIS REGRESSION EQUATION IS (SALES = 0.359826*MONTH CONST PERMITS + 1.999297)

SUMMARY OUTPUT Regression Statistics Multiple R 0.784387 R Square 0.615263 Adjusted R Square 0.567171 Standard Error 2.682271 Observations 10 ANOVA df SS MS F Significance F Regression 1 92.04338 92.04338 12.79344 0.007222 Residual 8 57.55662 7.194577 Total 9 149.6 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.999297 2.08196 0.960295 0.365027 -2.80171 6.800305 -2.80171 6.800305 X Variable 1 0.359826 0.1006 3.576792 0.007222 0.127841 0.59181 0.127841 0.59181