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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 ...
From the t-test, the difference between the group means is 6-2=4. From the regression, the slope is also 4 indicating that a 1-unit change in drug dose (from 0 to 1) gives a 4-unit change in mean word recall (from 2 to 6). The t-test p-value for the difference in means, and the regression p-value for the slope, are both 0.00805. The methods ...
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 ...
The Šidák correction is derived by assuming that the individual tests are independent. Let the significance threshold for each test be α 1 {\displaystyle \alpha _{1}} ; then the probability that at least one of the tests is significant under this threshold is (1 - the probability that none of them are significant).
One would not accept the null hypothesis, concluding that there is strong evidence that the expected values in the three groups differ. The p-value for this test is 0.002. After performing the F-test, it is common to carry out some "post-hoc" analysis of the group means. In this case, the first two group means differ by 4 units, the first and ...
Illustration of the power of a statistical test, for a two sided test, through the probability distribution of the test statistic under the null and alternative hypothesis. α is shown as the blue area, the probability of rejection under null, while the red area shows power, 1 − β, the probability of correctly rejecting under the alternative.
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 ...
In this respect, the classic permutation t-test shares the same weakness as the classical Student's t-test (the Behrens–Fisher problem). This can be addressed in the same way the classic t-test has been extended to handle unequal variances: by employing the Welch statistic with Satterthwaite adjustment to the degrees of freedom. [6]