🚀 go-pugleaf

I need help interpreting the results of stepwise regression with
SPlus.  I used forward and backward stepwise regression and below is
the last entry of the stepwise process before it spit out a linear
model.  My questions are:

1.  Why does the final linear model include variables that were
not in the last step, the model with the lowest AIC?


2.  How can I figure out how much variation each of the variables
contributes to the total variation?


Step:  AIC= 9.594


ExpDec ~ Ck + Yr + JD + JD2 + QNxtDy + QAve3 + WTDy + WTAve3 + DDCum
+
L + Yr:JD + QNxtDy:QAve3 + QAve3:JD + WTAve3:JD + L:JD


Single term deletions


Model:


ExpDec ~ Ck + Yr + JD + JD2 + QNxtDy + QAve3 + WTDy +WTAve3 + DDCum +
L + Yr:JD + QNxtDy:QAve3 +
       QAve3:JD + WTAve3:JD + L:JD


scale:  0.009112796


                           Df Sum of Sq      RSS       Cp


      <none>                             9.30242  9.59403


          Ck           1  1.239157   10.54158  10.81496
         JD2          1  0.389247    9.69167    9.96505
       WTDy         1  0.085947   9.38837    9.66175
       DDCum      1  2.607181   11.90960  12.18299
       Yr:JD         1  0.112556    9.41498    9.68836
QNxtDy:QAve3  1  1.081182   10.38360  10.65699
    QAve3:JD      1  0.038569    9.34099   9.61438
   WTAve3:JD    1  0.517758    9.82018   10.09357
        L:JD         1  0.116229    9.41865    9.69204


*** Linear Model ***


Call: lm(formula = ExpDec ~ Ck + Yr + JD + JD2 + QNxtDy +QAve3 + WTDy
+ WTAve3 + DDCum + L + Yr:JD +
      QNxtDy:QAve3 + QAve3:JD + WTAve3:JD + L:JD,


       data = global.02.03.07, na.action = na.exclude)


Residuals:


     Min       1Q            Median      3Q         Max


 -0.7327  -0.04916    0.001962    0.05493    0.2442


Coefficients:


                Value Std. Error  t value Pr(>|t|)


 (Intercept)        -0.6042   0.1279    -4.7227   0.0000
          Ck         -0.0472   0.0040   -11.6735   0.0000
          Yr           0.0566   0.0115     4.9032   0.0000
          JD           0.0099   0.0013     7.9236   0.0000
         JD2          0.0000   0.0000    -6.5426   0.0000
      QNxtDy      -1.0587   0.0593   -17.8450   0.0000
       QAve3         0.4737   0.0976     4.8542   0.0000
        WTDy        0.0212   0.0069     3.0744   0.0022
      WTAve3      -0.1433   0.0198    -7.2379   0.0000
       DDCum      -0.0012   0.0001   -16.9327   0.0000
           L           -0.0344   0.0111    -3.0999   0.0020
       Yr:JD         -0.0004   0.0001    -3.5182   0.0005
QNxtDy:QAve3  -0.6734   0.0618   -10.9041   0.0000
    QAve3:JD       0.0015   0.0007     2.0595   0.0397
   WTAve3:JD      0.0013   0.0002     7.5458   0.0000
        L:JD           0.0004   0.0001     3.5752   0.0004


Residual standard error: 0.09536 on 1023 degrees of freedom
Multiple R-Squared: 0.8761
F-statistic: 482.3 on 15 and 1023 degrees of freedom, the p-value