Give the four regression coefficient estimates, their standard errors and associated p-values. Data is below the image below

The attached {mesquitexlsx} data set gives for each of 20 mesquite trees the total leaf weight together 1with the longest and shortest canopy diameters, the canopy height and the tree height. The idea is to develop a model from which the total leaf weight of a mesquite tree could be estimated. Since leaf weight can be expected to be proportional to canopy volume, a model of the form Eirlcm, Cal = c x aces naturally rst presents itself. Here c, l, 232 and ,63 are unknown constants and c1 = longest canopy diameter .92 = shorest canopy diameter .93 = canopy heigiht. In order to bring linear model methodology to bear, a change to a logarithmic scale is made: EogY|ch c2, c3] 2 g + )31 log c1 + [32 log :32 + ,33 log c3 (1) 1with g 2 log c. Fit the model (1) to the day by ordinary (unweighted) least squares