![]() The sixth shows the p-value, which is derived from the cdf of F.The fifth shows the F statistic, which is the ratio of the MS's.The fourth shows the Mean Squares (MS) for each source, which is the ratio SS/df.The third shows the degrees of freedom (df) associated with each source.The second shows the Sum of Squares (SS) due to each source.The first shows the source of the variability.Variability due to the differences between the data in each column and the column mean (variability within groups).Variability due to the differences among the column means (variability between groups).The first figure is the standard ANOVA table, which divides the variability of the data in X into two parts: The anova1 function displays two figures. It is common to declare a result significant if the p-value is less than 0.05 or 0.01. The choice of a critical p-value to determine whether the result is judged "statistically significant" is left to the researcher. If the p-value is near zero, this casts doubt on the null hypothesis and suggests that at least one sample mean is significantly different than the other sample means. The function returns the p-value for the null hypothesis that all samples in X are drawn from the same population (or from different populations with the same mean). Performs a balanced one-way ANOVA for comparing the means of two or more columns of data in the m-by- n matrix X, where each column represents an independent sample containing m mutually independent observations. Anova1 (Statistics Toolbox) Statistics Toolbox
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