Question A Multiple regression is shown for a data set of yachts where the dependent variable is the price in thousands of dollars. Based on this output, which of the independent variables appear to be significantly helping to predict the price of a yacht, using a 0.10 level of significance? A) Age B) Age and length C) Rooms and Nav. Equip. D) Length and Nav. Equip. Regression Statistics Multiple R 0.82731 R Square 0.68445 Adjusted R Square 0.60030 Standard Error 37.40252 Observations 20 ANOVA df Significance F 0.00107 Regression Residual Total 8.13 MS 11378.94 1398.95 4 15 19 SS 45515.77 20984.23 66500.00 Intercept Rooms Age Length Nav. Equip. Coefficients 120.50886 7.46415 -1.7783 2.82719 0.35408 Standard Error 82.22254 12.24022 0.7179 1.40160 0.22411 t Stat P-value 1.46564 0.16339 0.60981 0.55112 -2.47713 0.02564 2.01711 0.06195 1.57995 0.13497 Lower 95% -54.74434 -18.62526 -0.33084 -0.16025 -0.12360 Upper 95% 295.76205 33.55355 -0.02482 5.81463 0.83176

Y7QGA0 The Asker · Probability and Statistics

A Multiple regression is shown for a data set of yachts where the dependent variable is the
price in thousands of dollars.

Based on this output, which of the independent variables appear to be significantly helping to
predict the price of a yacht, using a 0.10 level of significance?

A) Age
B) Age and length
C) Rooms and Nav. Equip.
D) Length and Nav. Equip.

Transcribed Image Text: Regression Statistics Multiple R 0.82731 R Square 0.68445 Adjusted R Square 0.60030 Standard Error 37.40252 Observations 20 ANOVA df Significance F 0.00107 Regression Residual Total 8.13 MS 11378.94 1398.95 4 15 19 SS 45515.77 20984.23 66500.00 Intercept Rooms Age Length Nav. Equip. Coefficients 120.50886 7.46415 -1.7783 2.82719 0.35408 Standard Error 82.22254 12.24022 0.7179 1.40160 0.22411 t Stat P-value 1.46564 0.16339 0.60981 0.55112 -2.47713 0.02564 2.01711 0.06195 1.57995 0.13497 Lower 95% -54.74434 -18.62526 -0.33084 -0.16025 -0.12360 Upper 95% 295.76205 33.55355 -0.02482 5.81463 0.83176
More
Transcribed Image Text: Regression Statistics Multiple R 0.82731 R Square 0.68445 Adjusted R Square 0.60030 Standard Error 37.40252 Observations 20 ANOVA df Significance F 0.00107 Regression Residual Total 8.13 MS 11378.94 1398.95 4 15 19 SS 45515.77 20984.23 66500.00 Intercept Rooms Age Length Nav. Equip. Coefficients 120.50886 7.46415 -1.7783 2.82719 0.35408 Standard Error 82.22254 12.24022 0.7179 1.40160 0.22411 t Stat P-value 1.46564 0.16339 0.60981 0.55112 -2.47713 0.02564 2.01711 0.06195 1.57995 0.13497 Lower 95% -54.74434 -18.62526 -0.33084 -0.16025 -0.12360 Upper 95% 295.76205 33.55355 -0.02482 5.81463 0.83176