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O CO 520 CHAPTER 14 | Introduction to Multiple Regression Height Diameter at breast height Bark thickness 122.0 193.5 d. Interpret the meaning of the coefficient of multiple determina- 166.5 tion in this problem. 82.0 1.2 133.5 e. Perform a residual analysis on the model and determine whether 156.0 the regression assumptions are valid. 172.5 f. Determine whether there is a significant relationship between 81.0 148.0 the height of redwood trees and the two independent variables 113.0 (breast-height diameter and bark thickness) at the 0.05 level of 84.0 significance. 164.0 203.3 g. Construct a 95% confidence interval estimate of the population 174.0 slope between the height of redwood trees and breast-height diam- 159.0 eter and between the height of redwood trees and the bark thickness. 205.0 223.5 h. At the 0.05 level of significance, determine whether each inde- 195.0 pendent variable makes a significant contribution to the regression 232.5 model. Indicate the independent variables to include in this model. 190.5 100.0 i. Construct a 95% confidence interval estimate of the mean height for trees that have a breast-height diameter of 25 inches and a bark thickness of 2 inches, along with a prediction interval for an individual tree. j. Compute and interpret the coefficients of partial determination. co k. What conclusions can you reach concerning the effect of the diame- ter of the tree and the thickness of the bark on the height of the tree