ANOVA test is really helpful to test more than one variable. It is the same with multiple two-sample t-tests. But it will result in fewer type I errors. Thus it is suitable for a range of issues. ANOVA compares each group as well as includes the spreading of the variance into diverse sources. In a nutshell, this test covers subjects, test groups from both between and within the groups.
There are types of ANOVA tests. The first is one-way ANOVA and the second is two-way ANOVA. The first ANOVA could also be the unidirectional ANOVA. There are also variations of ANOVA like in the MANOVA (multivariate ANOVA). MANOVA is different from ANOVA in the way that it tests multiple dependent variables perennially. Meanwhile, ANOVA tends to assess only one dependent variable at a time. In the analysis of variance tests, one-way and two-way reflect the number of independent variables.
The first type of ANOVA assesses the impact of a sole factor on a sole response variable, said Investopedia. So, it is to discern whether there is a similarity in the samples. Therefore, the one-way ANOVA indicates the statistical significance of the difference between the means of each independent groups.
Meanwhile, the two-way ANOVA is actually the one-way ANOVA’s extension. One-way ANOVA allows how one independent variable affects the dependent variable. Then, with the two-way ANOVA, there would be two independents. The epitome would be, two-way ANOVA allows a business to compare workforce based on two independent variables like experience and salary. The goal is to analyze the interaction between the two factors.