STATISTICAL TECHNIQUES AND TOOLS
ANALYSIS OF VARIANCE
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Detailed explanation-1: -The independent variable should have at least three levels (i.e. at least three different groups or categories). ANOVA tells you if the dependent variable changes according to the level of the independent variable.
Detailed explanation-2: -The groups to be compared are organized in separate aggregates. The script can handle 3 or four groups. If Merge columns is enabled, the data of all columns will be pooled, otherwise the ANOVA analysis is performed per column.
Detailed explanation-3: -In ANOVA, the dependent variable must be a continuous (interval or ratio) level of measurement. The independent variables in ANOVA must be categorical (nominal or ordinal) variables. Like the t-test, ANOVA is also a parametric test and has some assumptions. ANOVA assumes that the data is normally distributed.
Detailed explanation-4: -A One-Way ANOVA (Analysis of Variance) is a statistical technique by which we can test if three or more means are equal. It tests if the value of a single variable differs significantly among three or more levels of a factor.