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Partial Least SquaresAnalysis 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
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
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.