The t-test uses a T distribution. It checks if the difference between the means of two groups is statistically correct, based on sample averages and sample standard deviations, assuming unequal standard deviations. As part of the test, the tool also VALIDATE the test's assumptions, checks UNEQUAL standard deviations assumption, checks data for NORMALITY and draws a HISTOGRAM and a DISTRIBUTION.
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 mean involve independent samples (unpaired samples) or paired samples.
![T Test Calculator T Test Calculator](/uploads/1/2/5/3/125373407/484739558.png)
Paired t-tests are a form of, and have greater than unpaired tests when the paired units are similar with respect to 'noise factors' that are independent of membership in the two groups being compared. In a different context, paired t-tests can be used to reduce the effects of in an.Independent (unpaired) samples The independent samples t-test is used when two separate sets of samples are obtained, one from each of the two populations being compared.
For example, suppose we are evaluating the effect of a medical treatment, and we enroll 100 subjects into our study, then randomly assign 50 subjects to the treatment group and 50 subjects to the control group. In this case, we have two independent samples and would use the unpaired form of the t-test. The randomization is not essential here – if we contacted 100 people by phone and obtained each person's age and gender, and then used a two-sample t-test to see whether the mean ages differ by gender, this would also be an independent samples t-test, even though the data are observational.Paired samples.
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