Acronym for "Analysis of Variance", it is a parametric statistical test used to determine differences between two or more data sets. Importantly, certain criteria must be met before this test can be used. First, the individual data points must be independent (individual values do not depend on each other). Second, the variables measured must be continuous (having an infinite number of possible values). Third, the data must follow a normal Gaussian distribution. Fourth, the variance (spread of the data) of both data sets should be equivalent. There are different types of ANOVAS depending on what analysis is required: One-way ANOVA's compare multiple data sets along one category (ex. how different drugs [the category] affect blood pressure [the data sets]); Two-way (factorial) ANOVA's compare multiple data sets along two or more categories (ex. how two or more drugs provided to different age groups [the categories] affect blood pressure [the data sets]); Repeated measures ANOVA's compare multiple data sets at two or more time points (ex. how two or more drugs [the category] affect blood pressure of the same participantes at multiple time points [the data sets])