Analyze Variability

Coefficients Table - P-Values

  

Use the p-values (P) in the coefficients table to determine which of the effects in the model are statistically significant.

If there are significant interactions, you should look at these first because a significant interaction influences how you interpret the main effects. To use the p-value, you need to:

·    Identify the p-value for the effect you want to evaluate.

·    Compare this p-value to your a-level. A commonly used a-level is 0.05.

-    If the p-value is less than or equal to a, you can conclude that the effect is significant.

-    If the p-value is greater than a, you can conclude that the effect is not significant.

Example Output

 

Coded Coefficients for Ln(Std)

 

                             Ratio

Term                Effect  Effect     Coef  SE Coef  T-Value  P-Value   VIF

Constant                             0.3424   0.0481     7.12    0.001

Material           -0.9598  0.3830  -0.4799   0.0481    -9.99    0.000  1.00

InjPress           -0.1845  0.8315  -0.0922   0.0481    -1.92    0.113  1.00

InjTemp             0.0555  1.0571   0.0278   0.0481     0.58    0.589  1.00

CoolTemp           -0.1259  0.8817  -0.0629   0.0481    -1.31    0.247  1.00

Material*InjPress  -0.9918  0.3709  -0.4959   0.0481   -10.32    0.000  1.00

Material*InjTemp    0.1875  1.2062   0.0937   0.0481     1.95    0.109  1.00

Material*CoolTemp   0.0056  1.0056   0.0028   0.0481     0.06    0.956  1.00

InjPress*InjTemp   -0.0792  0.9239  -0.0396   0.0481    -0.82    0.448  1.00

InjPress*CoolTemp  -0.0900  0.9139  -0.0450   0.0481    -0.94    0.392  1.00

InjTemp*CoolTemp    0.0066  1.0066   0.0033   0.0481     0.07    0.948  1.00

Interpretation

For the insulation data, the manufacturer used least squares regression to run the analysis. The coefficients table shows the following effects:

·    Interaction effects - the model contains six 2-way interaction effects. The p-value for the interaction of material by injection pressure (0.000) is less than 0.05, which indicates that the effect of material depends on the injection pressure. Because the interaction is significant, you should interpret the interaction effect before the main effects.

·    Main effects - the model contains four main effects. The p-value for material (0.000) is less than 0.05, indicating that the effect is significant.

You may want to refit the model excluding the nonsignificant terms.