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  2. Wilks' theorem - Wikipedia

    en.wikipedia.org/wiki/Wilks'_theorem

    In practice, one will notice the problem if the estimate lies on that boundary. In that event, the likelihood test is still a sensible test statistic and even possess some asymptotic optimality properties, but the significance (the p -value) can not be reliably estimated using the chi-squared distribution with the number of degrees of freedom ...

  3. Welch–Satterthwaite equation - Wikipedia

    en.wikipedia.org/wiki/Welch–Satterthwaite_equation

    In statistics and uncertainty analysis, the Welch–Satterthwaite equation is used to calculate an approximation to the effective degrees of freedom of a linear combination of independent sample variances, also known as the pooled degrees of freedom, [1] [2] corresponding to the pooled variance.

  4. Allan variance - Wikipedia

    en.wikipedia.org/wiki/Allan_variance

    where s 2 is the sample variance of our estimate, σ 2 is the true variance value, df is the degrees of freedom for the estimator, and χ 2 is the degrees of freedom for a certain probability. For a 90% probability, covering the range from the 5% to the 95% range on the probability curve, the upper and lower limits can be found using the inequality

  5. Welch's t-test - Wikipedia

    en.wikipedia.org/wiki/Welch's_t-test

    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 ...

  6. Student's t-test - Wikipedia

    en.wikipedia.org/wiki/Student's_t-test

    The difference between the two sample means, each denoted by X i, which appears in the numerator for all the two-sample testing approaches discussed above, is ¯ ¯ = The sample standard deviations for the two samples are approximately 0.05 and 0.11, respectively. For such small samples, a test of equality between the two population variances ...

  7. Kruskal–Wallis test - Wikipedia

    en.wikipedia.org/wiki/Kruskal–Wallis_test

    The Kruskal–Wallis test by ranks, Kruskal–Wallis test (named after William Kruskal and W. Allen Wallis), or one-way ANOVA on ranks is a non-parametric statistical test for testing whether samples originate from the same distribution. [1] [2] [3] It is used for comparing two or more independent samples of equal or different sample sizes.

  8. Are Seed Oils Really Unhealthy? Dietitians Explain. - AOL

    www.aol.com/seed-oils-really-unhealthy...

    The bottom line: As with most things in the realm of nutrition, too much of any one food or type of food probably isn’t going to yield a balanced, wholesome diet. Consuming seed oils as part of ...

  9. Box–Muller transform - Wikipedia

    en.wikipedia.org/wiki/Box–Muller_transform

    The polar form takes two samples from a different interval, [−1,+1], and maps them to two normally distributed samples without the use of sine or cosine functions. The Box–Muller transform was developed as a more computationally efficient alternative to the inverse transform sampling method. [3] The ziggurat algorithm gives a more efficient ...