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[27] [29] [30] The nonparametric counterpart to the paired samples t-test is the Wilcoxon signed-rank test for paired samples. For a discussion on choosing between the t-test and nonparametric alternatives, see Lumley, et al. (2002). [19] One-way analysis of variance (ANOVA) generalizes the two-sample t-test when the data belong to more than ...
The one-sample version serves a purpose similar to that of the one-sample Student's t-test. [2] For two matched samples, it is a paired difference test like the paired Student's t-test (also known as the "t-test for matched pairs" or "t-test for dependent samples").
A paired difference test, better known as a paired comparison, is a type of location test that is used when comparing two sets of paired measurements to assess whether their population means differ. A paired difference test is designed for situations where there is dependence between pairs of measurements (in which case a test designed for ...
To design a test, Šidák correction may be applied, as in the case of finitely many t-test. However, when N ( n ) → ∞ as n → ∞ {\displaystyle N(n)\rightarrow \infty {\text{ as }}n\rightarrow \infty } , the Šidák correction for t-test may not achieve the level we want, that is, the true level of the test may not converges to the ...
Test name Scaling Assumptions Data Samples Exact Special case of Application conditions One sample t-test: interval: normal: univariate: 1: No [8]: Location test: Unpaired t-test: interval
Student's t-test assumes that the sample means being compared for two populations are normally distributed, and that the populations have equal variances. Welch's t-test is designed for unequal population variances, but the assumption of normality is maintained. [1] Welch's t-test is an approximate solution to the Behrens–Fisher problem.
If the paired observations are numeric quantities (such as the actual length of the hind leg and foreleg in the Zar example), and the differences between paired observations are random samples from a single normal distribution, then the paired t-test is appropriate. The paired t-test will generally have greater power to detect differences than ...
The Student's t distribution plays a role in a number of widely used statistical analyses, including Student's t test for assessing the statistical significance of the difference between two sample means, the construction of confidence intervals for the difference between two population means, and in linear regression analysis.