The linear effects of those two factors, though, are significant. If the sample data is in a matrix, y, providing the group information is optional. ![]() For example, Use this design when groups have different numbers of elements (unbalanced ANOVA). The p-value for the interaction term is not small, indicating little evidence that the effect of the car's year or manufacture ( when) depends on where the car was made ( org). The anova1 function treats the y values corresponding to the same value of group as part of the same group. It fits the following models for the i th group: Same mean. The list within each cell can be a vector, character array, or cell array of strings, and must have the same number of elements as X.Īs an example, consider the X and group inputs below. The aoctool function opens an interactive graphical environment for fitting and prediction with analysis of covariance (ANOCOVA) models. Each of the N cells in group contains a list of factor levels identifying the observations in X with respect to one of the N factors. The component ANOVA table contains statistics for the model terms, error, and total. The factors and factor levels of the observations in X are assigned by the cell array group. s stats( aov ) returns a component ANOVA table for the anova object aov. Performs a balanced or unbalanced multi-way ANOVA for comparing the means of the observations in vector X with respect to N different factors. ![]() P = anovan(X,group,' model',sstype,gnames,' displayopt') Measurement systems analysis Hypothesis testing Regression / ANOVA Process Capability. P = anovan(X,group,' model',sstype,gnames) Anovan (Statistics Toolbox) Statistics Toolbox
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