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 (x ₁ ), exposure time (x ₂ ), and pH value (x ₃ ). Data collected for each of 15 peat samples were used to fit the model

A summary of the regression results follows:

E ( y ) = β ₀ + β ₁ x ₁ + β ₂ x ₂ + β ₃ x ₃

A summary of the regression results follows:

y ̂ = –3,000 + 3.2 x ₁ – . x ₂ – 1.1 x ₃ R ² = .93

S _{β̂ 1} = 2.4 S _{β̂ 2} = .6 S _{β̂ 3} = .8

r ₁₂ = .92 r ₁₃ = .87 r ₂₃ = .81

Based on these results, the bioengineer concludes that none of the three independent variables, x ₁ , x ₂ , and x ₃ , is a useful predictor of carbohydrate amount, y . Do you agree with this statement?

Based on these results. the bioengineer concludes that none of the three independent variables, x ₁ , x ₂ , and x ₃ , is a useful predictor of carbohydrate amount. y . Do you agree with this statement? Explain.