Like z-tests,Â t-testsÂ are calculations used to test a hypothesis, but they are most useful when we need to determine if there is a statistically significant difference between two independent sample groups.Â In this article we will look at T.TEST in Excel.

A t-test asks whether a difference between the means of two groups is unlikely to have occurred because of random chance. Usually, t-tests are most appropriate when dealing with problems with a limited sample size (nÂ < 30).

Now you might think that comparing the averages are easy, but averages are affected by outliers and can give misleading results. You may also have situations where the sample and population sizes are different. Â Lets say you have a drug for the flu, and patients that take it get better on average in 3 days, and patients that donâ��t get better on average 5 days.Â The T. Test can be used to see if this difference if by fluke or because of the drug.

Another Example would be to test to see if the change in sales are down to a successful marketing campaign or if the change in sales happened by chance.

### Example

Our table of data represents the age of

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eturnerx (58)· 14 days agoT-Tests are for data we can assume is normally distributed. That applies for much human data, but isn't always true.

T-Tests are also not useful for ordinal (ranked, but the number doesn't represent the distance between the ranks) or nominal (category) based data.

The most common misuse I see of T-Tests is when examining Likert-like data (e.g. 0 = Never, 1 = Rarely, 2 = Sometimes, 3 = Often, 4 = Frequently, 5 = Always). This data is ordinal because it is ranked but the distance between ranks is not clear. For this kind, of data use something like: Wilcoxon or Mann-Whitney.

T-Test is still a great test to use!

paulag (70)· 14 days agoHay and thanks for visiting. Yes this is true, T.TESTS are not good for ordinal data at all. However it is good for the examples shown. I must check to see if excel has built in functions for Wilcoxon, although it might be a combination of functions.