WHAT IS ANOVA?

The acronym ANOVA refers to analysis of variance and is a statistical procedure used to test the degree to which two or more groups vary or differ in an experiment. In most experiments, a great deal of variance (or difference) usually indicates that there was a significant finding from the research. In this lesson, we will look at a detailed example of how an ANOVA works and how it can be applied to real life situations.

In the majority of experiments, you first need a null hypothesis and an alternative hypothesis. A null hypothesis is the assumption that there will be no differences between groups that are tested and therefore, no significant results will be revealed. The alternative hypothesis, on the other hand, is the hypothesis stating that there will be a difference between groups as indicated by the ANOVA performed on the data that is collected.

Let’s use an experiment scenario to help explain things. Imagine that you are running an experiment to see if there is a relationship between people’s religion and what they consider the ideal family size to be. You would likely do this by recruiting individuals from different religious groups and asking them to report what they consider the ideal number of children in a family should be. Let us further say that you ended up recruiting 10 Catholics, 10 Protestants, and 10 Jewish individuals to answer this question.

In this case, you have one independent variable, which is religion, that is thought to have an effect on the opinion of ideal family size, which is the dependent variable in this scenario. Additionally, this experiment includes three different levels of the independent variable. In this case, the three levels are the three different groups of religions.