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Sum of squares helps express the total variation that can be attributed to various predictors. The error sum of squares (SSE) is the sum of the squared residuals. In an ANOVA, Minitab separates the sums of squares into different components that describe the variation due to different sources.
Sum of squares function. To use this function, choose Calc > Calculator. Squares each value and calculates the sum of those squared values. That is, if the column contains x 1, x 2, ... , x n, then sum of squares calculates (x1 2 + x2 2 + ... + xn 2).
Sum of squares (SS) The sum of squares (SS) is the sum of squared distances, and is a measure of the variability that is from different sources.
Sum of squares (SS) In matrix terms, these are the formulas for the different sums of squares: Minitab breaks down the SS Regression or SS Treatments component into the amount of variation explained by each term using both the sequential sum of squares and adjusted sum of squares.
Sums of squares (SS) and standard deviations are closely related. Standard deviations are just sums of squares divided by the appropriate degrees of freedom. In This Topic
Sum of squares. The uncorrected sum of squares are calculated by squaring each value in the column, and then adding those squared values. For example, if the column contains x 1, x 2, ... , x n, then the sum of squares is calculated as (x 12 + x 22 + ... + x n2).
The within-cluster sum of squares is a measure of the variability of the observations within each cluster. In general, a cluster that has a small sum of squares is more compact than a cluster that has a large sum of squares.
The adjusted sum of squares is the amount of variation explained by a term, given all other terms in the model, regardless of the order that the terms enter the model. For example, if you have a model with three factors, X1, X2, and X3, the adjusted sum of squares for X2 shows how much of the remaining variation the term for X2 explains, given ...
The sum of squares (SS) is the sum of squared distances, and is a measure of the variability that is from different sources. Total SS indicates the amount of variability in the data from the overall mean.
Minitab squares each value in the column, then computes the sum of those squared values.