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Unpaired and paired two-sample t-tests

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  Unpaired and paired two-sample  t -tests [ edit ] Type I error of unpaired and paired two-sample  t -tests as a function of the correlation. The simulated random numbers originate from a bivariate normal distribution with a variance of 1. The significance level is 5% and the number of cases is 60. Power of unpaired and paired two-sample  t -tests as a function of the correlation. The simulated random numbers originate from a bivariate normal distribution with a variance of 1 and a deviation of the expected value of 0.4. The significance level is 5% and the number of cases is 60. Two-sample  t -tests for a difference in means involve independent samples (unpaired samples) or  paired samples . Paired  t -tests are a form of  blocking , and have greater  power  (probability of avoiding a type II error, also known as a false negative) than unpaired tests when the paired units are similar with respect to "noise factors" (see  confounde...
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Student's t-test

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  Student's  t -test 35 languages Article Talk Read Edit View history Tools From Wikipedia, the free encyclopedia A  t -test  is a type of statistical analysis used to compare the averages of two groups and determine whether the differences between them are more likely to arise from random chance. It is any  statistical hypothesis test  in which the  test statistic  follows a  Student's  t -distribution  under the  null hypothesis . It is most commonly applied when the test statistic would follow a  normal distribution  if the value of a  scaling term  in the test statistic were known (typically, the scaling term is unknown and is therefore a  nuisance parameter ). When the scaling term is estimated based on the  data , 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 populatio...
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