![]() ![]() 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. All options will perform a two-tailed test. Notice not all options are available if you enter means only.Įnter data for the test, based on the format you chose in Step 1.Ĭlick Calculate Now and View the results. Use our Ultimate Guide to t tests if you are unsure which is appropriate, as it includes a section on "How do I know which t test to use?". If you have already calculated these summary statistics, the latter options will save you time.Ĭhoose a test from the three options: Unpaired t test, Welch's unpaired t test, or Paired t test. The last two are for entering the means for each group, along with the number of observations (N) and either the standard error of that mean (SEM) or standard deviation of the dataset (SD) standard error. The first two options are for entering your data points themselves, either manually or by copy
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