Multifactor ANOVA

When more than one factor is present and the factors are crossed, a multifactor ANOVA is appropriate. Both main effects and interactions between the factors may be estimated. In a graphical representation of the results of an ANOVA the points are scaled so that any levels that differ by more than the difference exhibited in the distribution of the residuals are significantly different. 

Boron. There was no evidence of significant deviation from normality (p = 98%) of the B data. This was not the case for Zn and Sc where a significant (p = 3.78 10-10 and 1.25 10-6 respectively) deviation from normality was detected. The multifactor ANOVA was performed on the boron data, and a plot of residuals versus factor levels plot indicates a lack of homogeneity of the variances across different factor levels as can be seen in Figure 4.5.4. 

Use a commercial software package enabling multifactor ANOVA to decide whether there are systematic differences between the five charges at a significance level of a = 0.05. 

Effect of preconditioning on migration results. The effects of preconditioning and of migration test water were investigated using multifactor ANOVA (analysis of variance). This statistieal tool breaks the variability of data (pH, Al, Ca or K) into contributions due to various factors (preconditioning conditions and CO2 added in test water). 

Response Surfaces. 3. Basic Statistics. 4. One Experiment. 5. Two Experiments. 6. Hypothesis Testing. 7. The Variance-Covariance Matrix. 8. Three Experiments. 9. Analysis of Variance (ANOVA) for Linear Models. 10. A Ten-Experiment Example. 11. Approximating a Region of a Multifactor Response Surface. 12. Additional Multifactor Concepts and Experimental Designs. Append- ices Matrix Algebra. Critical Values of t. Critical Values of F, a = 0.05. Index. 

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