Compare the following models based on goodness of fit: Model A: y=1+2lnx2+uRA2=0.75 Adjusted- RA2=0.74 Model B: In y=1+2x2+3x3+vRB2=0.74 Adjusted- RB2=0.73 Model C: lny=1+2x2+3x3+4lnx1+eRB22=0.78 Adjusted-R R2=0.72 Model D: y=1+y4x4+wRD2=0.76 Adjusted- RD2=0.75 a. B>C \& D>A; and other combinations cannot be compared b. C>B \& D>A; and other combinations cannot be compared c. C>D>A>B d. D>A>B>C The variables in our dataset include the college grade point average (colGPA), high school GPA (hsGPA), and achievement test score (ACT) for a sample of 141 students from a large university; both college and high school GPAs are on a four-point scale. We estimate the following model by OLS: colGPA=1+2hsGPA+2ACT+1 and obtain the following parameter estimates 1=0,6,1=0.35, and 2=0.032. Predict the college GPA of a student with high school GPA of 3.3 and ACT score of 31