Question 4 [Corresponds to Question 10 in Mendenhall and Sincich Text] Steam Processing of Peat: A bioengineer wants to model the amount (y) of carbohydrate solubilized during steam processing of peat as a function of temperature (x1), exposure time (x2), and pH value (x3). Data collected for each of 15 peat samples were used to fit the model E(y) Bo+B1x1 + 2x2 + B3x3 A summary of the regression results follows: = -3,000+ 3.2x1.4x2 -1.1x3 R = .93 . Sp = 2.4 . SB = .6 S = .8 112 = .92 13.87 123= .81 a) [3 points] Based on these results, the bioengineer concludes that none of the three independent variables x1, x2 and x3 is a useful predictor of carbohydrate amount? Do you agree with this statement? EXPLAIN why or why not. b) [7 points] Is there evidence of Multicollinearity? DISCUSS *To receive full credit; your discussion should utilize evidence from: Correlations between pairs of independent variables Individual t tests of independent variables (hint: calculate these] Multiple coefficient of determination