Validating the effect of changes with the t-test
When measuring the effects of certain actions applied to a given population of users, we need to validate that these actions have actually affected the target groups in a significant manner. To be able to do this, we can use the t-test.
A t-test is a statistical test that is used to compare the means of two groups to ascertain whether a method or treatment has an impact on the population of interest or whether two groups differ from one another; it is frequently employed in hypothesis testing.
When the datasets in the two groups don’t relate to identical values, separate t-test samples are chosen independently of one another. They might consist of two groups of randomly selected, unrelated patients to study the effects of a medication, for example. While the other group receives the prescribed treatment, one of the groups serves as the control group and is given a placebo. This results in two separate sample sets that are...
