Question

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.9448
R2	0.8927
Adj. R2	0.8853
SY.X	133.14
N	32
ANOVA
	df	SS	MS	F	P-value
Regression	2	4277160	2138580	120.6511	0.0000
Residual	29	514034.5	17725.33
Total	31	4791194
	Coeff.	Std. Err.	t Stat	P-value	Lower 95%	Upper 95%
Intercept	-1336.72	173.3561	-7.71084	0.0000	-1691.2753	-982.16877
X1	12.7362	0.90238	14.114	0.0000	10.890623	14.5817752
X2	85.81513	8.705757	9.857286	0.0000	68.009851	103.620414

With respect to the null hypothesis for the regression model, we can conclude that

a. The regression relationship is statistically significant

b. A second-order model is useful for predicting auction price

c. The model coefficients are not statistically significantly different from zero

d. None of the above is correct

We can also conclude, from the results, that

a. About 89% of the variation of the auction prices about their mean can be explained by the model

b. About 89% of the variation of the auction prices about their predicted values can be explained by the model

c. Prediction of auction price with the model is impossible since age of clock and number of bidders do not provide 100% of the variation of Y

d. a and c are both correct

e. b and c are both correct

Answer 1