Search results
Results from the WOW.Com Content Network
The independent samples t-test is used when two separate sets of independent and identically distributed samples are obtained, and one variable from each of the two populations is 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 ...
In statistics, Welch's t-test, or unequal variances t-test, is a two-sample location test which is used to test the (null) hypothesis that two populations have equal means. It is named for its creator, Bernard Lewis Welch , and is an adaptation of Student's t -test , [ 1 ] and is more reliable when the two samples have unequal variances and ...
In statistics, the Jonckheere trend test [1] (sometimes called the Jonckheere–Terpstra [2] test) is a test for an ordered alternative hypothesis within an independent samples (between-participants) design. It is similar to the Kruskal-Wallis test in that the null hypothesis is that several independent samples are from the same population ...
Unpaired samples are also called independent samples. Paired samples are also called dependent. Finally, there are some statistical tests that perform analysis of relationship between multiple variables like regression. [1] Number of samples: The number of samples of data. Exactness: A test can be exact or be asymptotic delivering approximate ...
GUI Features (features available via R or SPSS Syntax not listed) JASP 0.18.2: SPSS 29: JASP 0.18.2: SPSS 29: Analysis: Classic: Classic: Bayesian: Bayesian: Acceptance Sampling X (repeated) (M)AN(C)OVA and non-parametrics ( ) ( ) Audit - Statistical Methods for Auditing X X Bain - Bayesian informative hypotheses evaluation X
Most frequently, t statistics are used in Student's t-tests, a form of statistical hypothesis testing, and in the computation of certain confidence intervals. The key property of the t statistic is that it is a pivotal quantity – while defined in terms of the sample mean, its sampling distribution does not depend on the population parameters, and thus it can be used regardless of what these ...
A paired difference test is designed for situations where there is dependence between pairs of measurements (in which case a test designed for comparing two independent samples would not be appropriate). That applies in a within-subjects study design, i.e., in a study where the same set of subjects undergo both of the conditions being compared.
The test is named after Frank Wilcoxon (1892–1965) who, in a single paper, proposed both it and the rank-sum test for two independent samples. [3] The test was popularized by Sidney Siegel (1956) in his influential textbook on non-parametric statistics. [4] Siegel used the symbol T for the test statistic, and consequently, the test is ...