Partial Least Squares

Analysis of Variance Tables

  

Minitab displays one analysis of variance table per response based on the selected model. The table shows the amount of variation in the response explained by the model and the amount of variation left unexplained.

The value under P (p-value) is the most important result to consider in this table. Use the p-value to analyze whether the regression coefficients are significantly different from zero. If the p-value is smaller than a preselected a-level, you can deduce that at least one coefficient is not zero. A commonly used a-level is 0.05.

Example Output

Analysis of Variance for Moisture

 

Source          DF       SS       MS      F      P 

Regression      10  468.516  46.8516  61.46  0.000

Residual Error  43   32.777   0.7623

Total           53  501.293

 

 

Analysis of Variance for Fat

 

Source          DF       SS       MS      F      P

Regression      10  266.378  26.6378  36.89  0.000

Residual Error  43   31.050   0.7221

Total           53  297.428

Interpretation

In this example, Minitab displays two analysis of variance tables - one for moisture and one for fat. The p-values for both responses are less than 0.0005, indicating that the model is significant and at least one regression coefficient is not zero.