A forester wishes to predict the volume (in cubic feet) of usable lumber in a certain species of trees from the height (in feet) and diameter (in inches) of the trees. The height and diameter of 31 trees of a certain species were measured, the trees were cut down, and the volume of usable lumber was determined. The multiple linear regression model
Volume = β0 + β1(Diameter) + β2(Height) + βi
is assumed to hold, where the deviations i are independent and Normally distributed with mean 0 and standard deviation . This model is fit to the data using the method of least squares using statistical software, and the following parameter estimates and their standard errors are obtained.
![802_Example on Multiple linear regression model.gif](https://mywordsolution.com/CMSImages/802_Example%20on%20Multiple%20linear%20regression%20model.gif)
Based on these results, a 99% confidence interval for β0 is found to be -57.99 ± 23.87. We may conclude
A. if we tested the hypotheses H 0: β0 = 0, Ha: β0 ≠ 0, the P-value would be less than 0.01.
B. the estimate of β0 would tell us the volume of a tree of this species when height and diameter are 0.
C. Both choices are correct.