![]() ![]() If the number of degrees of freedom is large (>30), which generically happens for large samples, the t-Student distribution is practically indistinguishable from N(0,1). This distribution has a shape similar to N(0,1) (bell-shaped and symmetric) but has heavier tails. If there are d degrees of freedom, then the distribution of the test statistics is the t-Student distribution with d degrees of freedom. The degrees of freedom are essential, as they determine the distribution followed by your t-score (under the null hypothesis). Again, the exact formula depends on the t-test you want to perform - check the sections below for details. In the simplest case, the number of degrees of freedom equals your sample size minus the number of parameters you need to estimate. The degrees of freedom are the number of observations in a sample that are free to vary as we estimate statistical parameters. ![]() The exact formula depends on the t-test type - check the sections dedicated to each particular test for more details.ĭetermine the degrees of freedom for the t-test: Use a one-tailed t-test if you want to test whether this mean (or difference in means) is greater/less than the pre-set value.įormulas for the test statistic in t-tests include the sample size, as well as its mean and standard deviation. Use a two-tailed t-test if you only care whether the population's mean (or, in the case of two populations, the difference between the populations' means) agrees or disagrees with the pre-set value. These next steps will tell you how to calculate the p-value from t-test or its critical values, and then which decision to make about the null hypothesis. So, you've decided which t-test to perform.
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