Unlike an ANOVA, however, an ANCOVA includes one or more covariates, which can help us better understand how a factor impacts a response variable after accounting for some covariate(s).Įxample: Consider the same example we used in the One-Way ANOVA. You can conduct a two-way ANOVA to determine if exercise and gender impact weight loss and to determine if there is an interaction between exercise and gender on weight loss.Īn ANCOVA (“Analysis of Covariance”) is also used to determine whether or not there is a statistically significant difference between the means of three or more independent groups. In this case, the two factors you’re studying are exercise and gender and your response variable is weight loss (measured in pounds). Two-Way ANOVA: Used to determine how two factors impact a response variable, and to determine whether or not there is an interaction between the two factors on the response variable.Įxample: You want to determine if level of exercise (no exercise, light exercise, intense exercise) and gender (male, female) impact weight loss. At the end of the month, all of the students take the same exam. You want to know whether or not the studying technique has an impact on exam scores so you conduct a one-way ANOVA to determine if there is a statistically significant difference between the mean scores of the three groups. Each group uses a different studying technique for one month to prepare for an exam. One-Way ANOVA: Used to determine how one factor impacts a response variable.Įxample: You randomly split up a class of 90 students into three groups of 30. The two most common types of ANOVAs are the one-way ANOVA and two-way ANOVA. ANOVAĪn ANOVA (“Analysis of Variance”) is used to determine whether or not there is a statistically significant difference between the means of three or more independent groups. This tutorial explains the differences between the statistical methods ANOVA, ANCOVA, MANOVA, and MANCOVA.
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