Question 4 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 pl value (x3). Data collected for each of 15 peat samples were used to fit the model E(y) = Bo+ Bix1 + B2x2 + ByX3 A summary of the regression results follows: p = -3,000 + 3.2x1 - .4x2 - 1.1x3 R2 = .93 $3. =2.4 $3, =.6 57, = .8 712 = .92 713 = .87 123 = .81 a) 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. 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