There are three types of t-tests: the one-sample t-test, the two-sample t-test, and the paired samples t-test. The one-sample t-test is used to test whether a sample mean is statistically different from a known population mean. The two-sample t-test is used to test whether there is a significant difference between the means of two independent groups. The paired samples t-test is used to compare the means of two related groups.
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A) One-sample t-test
The one-sample t-test is used to test whether a sample mean is statistically different from a known population mean.
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B) Two-sample t-test
The two-sample t-test is used to test whether there is a significant difference between the means of two independent groups
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If there are more than two groups, a pair-wise two-sample t-test can be performed, but a better approach is to use ANOVA (Analysis of Variance). If the variances of the two samples being compared are different, the unequal variances t-test (Welch's t-test) should be used.
C) Paired samples t-test
The paired samples t-test is used to compare the means of two related groups.
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Assumptions of t-test
Assumptions of the t-test include normally distributed data, random sampling, and homogeneity of variance. If these assumptions are not met, non-parametric tests should be used instead.