Multiple regression was run for a random sample of 21 redwood trees, and the following output information was generated. The dependent variable was the height (in feet) of a tree and independent variables were diameter (in inches) and bark thickness (in inches). Regression Statistics: Multiple R=0.8864 R Square =0.7858 Adjusted R Squared =0.7620 Standard Error =22.5982 Observations =21 Coefficients: Intercept =62.141 Diameter =2.057 Bark Thickness =15.642 Based on the sample regression coefficient of Diameter, we estimate that: holding bark thickness constant, as the diameter increases by 1 inch, the height increases by 2.057 inches. holding bark thickness constant, as the height increases by 1 foot, the diameter increases by 2.057 inches. holding bark thickness constant, as the height increases by 1 foot, the diameter increases by 2.057 feet. holding bark thickness constant, as the diameter increases by 1 inch, the height increases by 2.057 feet