Shown below is output from two Excel regression analyses on the same problem. The first output was done on a “full” model. In the second output, the variable with the smallest absolute t value has been removed, and the regression has been rerun like a second step of a backward elimination process. Examine the two outputs. Explain what happened, what the results mean, and what might happen in a third step.

FULL MODEL Regression Statistics Multiple R 0.567 R Square 0.321 Adjusted R Square 0.208 Standard Error 159.681 Observations 29 ANOVA Significance F df SS MS F Regression 4 289856.08 Residual 24 611955.23 72464.02 25498.13 2.84 0.046 Total 28 901811.31 Coefficients Standard Error t Stat P-value Intercept 336.79 124.0800 2.71 0.012 X 1.65 1.7800 0.93 0.363 X2 -5.63 13.4700 -0.42 0.680 X3 0.26 1.6800 0.16 0.878 185.50 66.2200 2.80 0.010