In this guide, we’ll lay out everything you need to know about t tests, including providing a simple workflow to determine what t test is appropriate for your particular data or if you’d be better suited using a different model.Ī t test is a statistical technique used to quantify the difference between the mean (average value) of a variable from up to two samples (datasets). All t tests are used as standalone analyses for very simple experiments and research questions as well as to perform individual tests within more complicated statistical models such as linear regression. The characteristics of the data dictate the appropriate type of t test to run. The t test is especially useful when you have a small number of sample observations (under 30 or so), and you want to make conclusions about the larger population. The t test is one of the simplest statistical techniques that is used to evaluate whether there is a statistical difference between the means from up to two different samples.
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