Understanding ANOVA
In this blog, you are going to find answers to the below questions.
- What is ANOVA?
- What are the assumptions of ANOVA?
- In which situations is the ANOVA used?
- What is the difference between Student’s T-test and ANOVA?
What Is ANOVA?
ANOVA is a statistical test that is used to evaluate the difference among the means of three or more groups.
Assumptions of ANOVA
- Populations are normally distributed.
ANOVA can only be applied to data that are normally distributed so we need to run a normality test. However, ANOVA test is robust to the assumption of normality. It works even if the distributions are not perfectly normal.
- Populations have equal variances.
ANOVA can only be applied to samples with the same variance. We need to run a Leven’s test to check the homogeneity of variance.
- Samples are randomly and independently drawn.
We need to check the experimental design to determine if samples are randomly selected.
