12 Redwood scenario. A forest management company wished to develop a model to assist in estimating the heights of the trees in a tract of California redwood trees. For a random sample of 21 redwood trees in the tract were determined the height (in feet), diameter (in inches) five feet from the base of the tree, and the bark thickness (in inches) five feet from the base of the tree. Below are the results of a regression analysis on this data using a model specification of Height = P, + B, Diameter + ,Bark Thickness + E. [source: Adapted from Berenson et al (2006)] Regression Statistics Multiple R 0.8864 R Square 0.7858 Adjusted R Squ 0.7620 Standard Error 22.5982 Observations 21 ANOVA df SS MS F Significance F Regression 2 33718.478 16859.24 33.0135 9.4991E-07 Residual 18 9192.189 510.6772 Total 20 42910.667 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 62.141 13.503 4.602 0.000221 33.772 90.510 Diameter 2.057 0.443 4.645 0.000201 1.126 2.987 Bark Thickness 15.642 7.148 2.188 0.042087 0.624 30.660