You need to select a significance threshold for your P value (often 0.05) before doing the test. The three different options for t tests have slightly different interpretations, but they all hinge on hypothesis testing and P values. These (and the ultimate guide to t tests) go into detail on the basic assumptions underlying any t test: Here are our analysis checklists for unpaired t tests and paired t tests, which are the two most common.

Assumptions of t testsīecause there are several versions of t tests, it’s important to check the assumptions to figure out which is best suited for your project. Since t tests compare means of continuous variable between groups, contingency tables use methods such as chi square instead of t tests. In contrast, t tests compare means between exactly two groups.įinally, contingency tables compare counts of observations within groups rather than a calculated average.

While t tests are part of regression analysis, they are focused on only one factor by comparing means in different samples.ĪNOVA is used for comparing means across three or more total groups. Here’s how to keep them all straight.Ĭorrelation and regression are used to measure how much two factors move together. In addition to the number of t test options, t tests are often confused with completely different techniques as well.

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