Student's t-test

Student's t-test is a <a href="/facts/Statistical_test/yv9RPF6U">statistical test</a> used to test whether the difference between the response of two groups is <a href="/facts/Statistical_significance/PMxjdlAu">statistically significant</a> or not. It is any <a href="/facts/Statistical_hypothesis_testing/yv9RPF6U">statistical hypothesis test</a> in which the <a href="/facts/Test_statistic/IBwfN5Kx">test statistic</a> follows a <a href="/facts/Student%27s_t-distribution/DeT1SDqH">Student's t-distribution</a> under the <a href="/facts/Null_hypothesis/C8NwSE9J">null hypothesis</a>. It is most commonly applied when the test statistic would follow a <a href="/facts/Normal_distribution/UapjjPyQ">normal distribution</a> if the value of a <a href="/facts/Scale_parameter/6lxcyKUf">scaling term</a> in the test statistic were known (typically, the scaling term is unknown and is therefore a <a href="/facts/Nuisance_parameter/acJWVqxj">nuisance parameter</a>). When the scaling term is estimated based on the <a href="/facts/Data/AUBFN97o">data</a>, the test statistic—under certain conditions—follows a Student's t distribution. The t-test's most common application is to test whether the means of two populations are significantly different. In many cases, a <a href="/facts/Z-test/qr6bM4a6">Z-test</a> will yield very similar results to a t-test because the latter converges to the former as the size of the dataset increases.

Student's t-test open-in-new

Student's t-test