t-test Assumptions
The main idea behind the t-test is that it follows the t-distribution. For it to be true, a few important assumptions are made:
- Homogeneity of Variance. The variances of the two compared groups should be approximately the same;
- Normality. Both samples should roughly follow a Normal distribution;
- Independence. The samples need to be independent, implying that the values in one group shouldn't be influenced by those in the other group.
It's important to note that the t-test may yield inaccurate results if these assumptions are not met.
There are different types of t-tests that handle violations of some of the assumptions:
- If the variances are different, you can run Welch's t-test. Its idea is the same. The only thing that differs is the degrees of freedom.
Performing Welch's t-test instead of the ordinary t-test in Python is as easy as setting
equal_var=False; - If samples are not independent(for example, if you want to compare the means of the same group at different time periods), you can run a paired t-test. A paired t-test will be discussed in a later chapter.
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The main idea behind the t-test is that it follows the t-distribution. For it to be true, a few important assumptions are made:
- Homogeneity of Variance. The variances of the two compared groups should be approximately the same;
- Normality. Both samples should roughly follow a Normal distribution;
- Independence. The samples need to be independent, implying that the values in one group shouldn't be influenced by those in the other group.
It's important to note that the t-test may yield inaccurate results if these assumptions are not met.
There are different types of t-tests that handle violations of some of the assumptions:
- If the variances are different, you can run Welch's t-test. Its idea is the same. The only thing that differs is the degrees of freedom.
Performing Welch's t-test instead of the ordinary t-test in Python is as easy as setting
equal_var=False; - If samples are not independent(for example, if you want to compare the means of the same group at different time periods), you can run a paired t-test. A paired t-test will be discussed in a later chapter.
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