Levene's Test

Our next step after visualization will be a statistical check of the equality of variances for the control and test groups.

For this, we need the Levene's test. It is used to test the null hypothesis that the variances are equal. By comparing the variances in both groups, the test uses a statistic based on the standard deviation.

It's called the F-statistic. If the obtained value of the F-statistic exceeds the critical value, this indicates significant differences in the variances of the groups.

Let's do a Levene's test for the 'Impression'speakers. Let's start with hypotheses:

H₀: The variances in both groups are the same;

Hₐ: Variances differ between groups.

Let's take a look at the code. The syntax is very simple:

As you can see, the p-value is much higher than 0.05. This means that we do not have enough statistical evidence to reject the null hypothesis of equality of variances. There is no statistically significant difference between the variances of the two samples.

Now let's draw a violin plot and a swarm plot for the 'Click' columns of both datasets:

Are the variances equal? Let's do a Levene test for the 'Click' columns of both datasets:

We need an understanding of whether the variances are equal to conduct a T-test. In the case of inequality of variances, we will use a modification of the T-test. Therefore, the Levene test is an important part of A/B testing. As you can see, the variances for these two columns are statistically different. Now it's your turn!