Analysis of Variance - An ANOVA is a tabular presentation of the Sum of Squares (SS;variance) attributed to the model, the Sum of Squares attributed to error (Pure error and Lack of Fit error). and the Total Sum of Squares from the data. F-statistics on the significance of the regression model are included.
Two models are generally used:
1. Classification model, OR
2. Analysis model.
Classification models are generally restricted to a one- or two-way classification of complete and balanced data. A one-way classification may be based on a single factor or may be based on a main factor and a blocking factor, where the blocking factor is treated as a random factor. A two-way classification is based on two fixed effect main factors.
The descriptions "Factorial Analysis of Variance" or "Regression Variance" are sometimes used for the sum of squares attributed to a parameter in a regression. While the SUM OF SQUARES may be the same, the Degrees of freedom for an ANOVA are different from those associated with a regression parameter.
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