Polynomial Regression
Getting Slope, Y Intercept and Model
Utility Test
Confidence Interval for
average y and Prediction Interval for next y

Getting Slope, Y Intercept and
Model Utility Test

Regression Analysis: Score2 versus
Score1, Score1squared
The
regression equation is
Score2 =
1.06 + 0.241 Score1 - 0.0021 Score1squared
Predictor Coef SE Coef T P
Constant
1.0640 0.3202 3.32 0.016
Score1
0.2412 0.1315 1.83 0.116
Score1squared -0.00209 0.01155
-0.18 0.863
S =
0.137256 R-Sq = 95.7% R-Sq(adj) = 94.3%
Analysis of
Variance
Source DF SS MS F P
Regression 2 2.5425 1.2713 67.48 0.000
Residual
Error 6 0.1130 0.0188
Total
8 2.6556
Notice that in this case, the p-value for the squared term is
very high. This means that there is not sufficient evidence that the Beta2 (the
slope term for the squared term) is sufficiently different from zero. The
regression should be rerun without the squared term.
Confidence Interval for average y and Prediction Interval for next y

Predicted
Values for New Observations
New
Obs Fit SE Fit 95% CI
95% PI
1
1.5380 0.1188 (1.2473, 1.8287) (1.0938, 1.9822)
Values of
Predictors for New Observations
New
Obs Score1 Score1squared
1 2.00 4.00