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Shown below is the output of two regression analyses on the same problem. The first output was done on a full model. In the second
Shown below is the output of two regression analyses on the same problem. The first output was done on a "full" model. In the second output, the variable with the highest p-value was removed and the regression has been rerun. Examine the two outputs.
Independent Variables | Coefficients | p-value |
---|---|---|
Intercept | 336.790 | 0.012 |
X1 | 1.650 | 0.363 |
X2 | -5.630 | 0.680 |
X3 | 0.260 | 0.878 |
X4 | 185.500 | 0.010 |
Independent Variables | Coefficients | p-value |
---|---|---|
Intercept | 342.919 | 0.006 |
X1 | 1.834 | 0.174 |
X2 | -5.749 | 0.667 |
X4 | 181.220 | 0.005 |
- Is Model 2 better than Model 1? Explain why. What is the most significant variable in the regression?
- Suppose we continue with this process of backward elimination where we remove the variable with the highest p-value. Which variable is likely to become newly significant as a result of this step? Does this imply that we have a better model?
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