2. In a classical experiment carried out from 1918 to 1934, apple trees of different rootstocks were compared (Andrews and Herzberg 1984, pp. 357-360). The variables analyzed were y1 = trunk girth at 4 years (mm x 100) y2 = extension growth at 4 years (m) y3 = trunk girth at 15 years (mm x 100) y4 = weight of tree above ground at 15 years (1b x 1000) (a) Using the SAS output below, carry out tests of significance for the discriminant functions and find the relative importance of each as in di Di=ldi' i = 1 , ..., s where & are the eigenvalues of the matrix E- H (our textbook calls this W-B). Do these two procedures agree to the number of important discriminant functions? The CANDISC Procedure Eigenvalues of Inv(E)*H CanRsq/(1-CanRsq) Test of HO: The canonical correlations in the current row and all that follow are zero Adjusted Approximate Squared Canonical Canonical Standard Canonical Likelihood Approximate Correlation Correlation Error Correlation Eigenvalue |Difference Proportion Cumulative Ratio F Value Num DF Den DF Pr > 1 0.807623 0.770467 0.050724 0.652255 1.8757 .0850 0.6421 0.6421 0.15400767 4.94 20 130.3 <.0001 the standardized coefficients are below. comment on contribution of variables to separation groups. pooled within-class canonical variable can1 can2 can3 can4 y1 y2 y a classification analysis was performed apple trees data set from previous problem. below linear functions. discriminant function for rootstock constant suppose that we had tree unknown with following values variables: y3="4.58," y4="0.666" what type would this be classified as is table. results. could it improved using quadratic discrimination why or not number observations and percent into total priors error count estimates discrim procedure test homogeneity within covariance matrices rate chi-square df pr> ChiSq Priors 0.1667 0.1667 0.1667 0.1667 0.1667 0.1667 44.018035 50 0.7110