In statistical hypothesis testing, a uniformly most powerful (UMP) test is a hypothesis test which has the greatest power 1 − β {\displaystyle 1-\beta...

test Sample size – Statistical considerations on how many observations to makePages displaying short descriptions of redirect targets Uniformly most powerful...

chi-squared test. Fisher information Uniformly most powerful test Score (statistics) Sup-LM test Rao, C. Radhakrishna (1948). "Large sample tests of statistical...

Shapiro–Wilk test is a test of normality. It was published in 1965 by Samuel Sanford Shapiro and Martin Wilk. The Shapiro–Wilk test tests the null hypothesis...

describes the existence and uniqueness of the likelihood ratio as a uniformly most powerful test in certain contexts. It was introduced by Jerzy Neyman and Egon...

η(θ) is non-decreasing. As a consequence, there exists a uniformly most powerful test for testing the hypothesis H0: θ ≥ θ0 vs. H1: θ < θ0. Exponential families...

hypothesis test in which the test statistic follows a Student's t-distribution under the null hypothesis. It is most commonly applied when the test statistic...

A chi-squared test (also chi-square or χ2 test) is a statistical hypothesis test used in the analysis of contingency tables when the sample sizes are large...

Epps and Pulley, Henze–Zirkler, BHEP test). The energy and the ECF tests are powerful tests that apply for testing univariate or multivariate normality...

the test statistic (see Test with estimated parameters). Various studies have found that, even in this corrected form, the test is less powerful for testing...

with extremely low levels of heavier elements Uniformly most powerful test, in statistical hypothesis testing Uridine monophosphate, a nucleotide Utility...

Likelihood-ratio test Wald test Score test Sequential probability ratio test Uniformly most powerful test Exact test Confidence interval Prediction interval...

variable. Tests whose results are of continuous values, such as most blood values, can artificially be made binary by defining a cutoff value, with test results...

A/B testing (also known as bucket testing, split-run testing or split testing) is a user-experience research method. A/B tests consist of a randomized...

given value of the parameter(s) being tested, contained in the alternative hypothesis. Uniformly most powerful test (UMP) Bootstrap-based resampling methods...

The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another, first proposed in...

An F-test is a statistical test that compares variances. It is used to determine if the variances of two samples, or if the ratios of variances among multiple...

67 and not be normally distributed (so the above test would produce a false positive). A better test of normality, such as Q–Q plot would be indicated...

dominance, Dunn's test, pairwise Mann–Whitney tests with Bonferroni correction, or the more powerful but less well known Conover–Iman test are sometimes used...

significance testing: as F becomes so small that the group means are much closer together than we would expect by chance, a significance test might indicate...

methods are proven to be the most powerful tests through methods such as the Neyman–Pearson lemma and the Likelihood-ratio test. Another justification for...

In statistics a minimum-variance unbiased estimator (MVUE) or uniformly minimum-variance unbiased estimator (UMVUE) is an unbiased estimator that has...

the Holm–Bonferroni method, which uniformly delivers more power than the simple Bonferroni correction, by testing only the lowest p-value ( i = 1 {\displaystyle...

Jackknife Testing hypotheses 1- & 2-tails Power Uniformly most powerful test Permutation test Randomization test Multiple comparisons Parametric tests Likelihood-ratio...

lemma states that this likelihood-ratio test is the most powerful among all level α {\displaystyle \alpha } tests for this case. The likelihood ratio is...

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data. Multivariate normality tests include the Cox–Small test and Smith and Jain's adaptation of the Friedman–Rafsky test created by Larry Rafsky and Jerome...

Suppose that we have a sample of 99 test scores with a mean of 100 and a standard deviation of 1. If we assume all 99 test scores are random observations from...

are ranked but not numerical (e.g. working out a median grade when student test scores are graded from F to A), although the result might be halfway between...

case. Tests in regression Goldfeld–Quandt test Park test Glejser test Harrison–McCabe test Breusch–Pagan test White test Cook–Weisberg test Tests for grouped...