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  2. Fisher's method - Wikipedia

    en.wikipedia.org/wiki/Fisher's_method

    Under Fisher's method, two small p-values P 1 and P 2 combine to form a smaller p-value.The darkest boundary defines the region where the meta-analysis p-value is below 0.05.. For example, if both p-values are around 0.10, or if one is around 0.04 and one is around 0.25, the meta-analysis p-value is around 0

  3. Fisher's exact test - Wikipedia

    en.wikipedia.org/wiki/Fisher's_exact_test

    Fisher's exact test (also Fisher-Irwin test) is a statistical significance test used in the analysis of contingency tables. [ 1 ] [ 2 ] [ 3 ] Although in practice it is employed when sample sizes are small, it is valid for all sample sizes.

  4. F-test - Wikipedia

    en.wikipedia.org/wiki/F-test

    Common examples of the use of F-tests include the study of the following cases . One-way ANOVA table with 3 random groups that each has 30 observations. F value is being calculated in the second to last column The hypothesis that the means of a given set of normally distributed populations, all having the same standard deviation, are equal.

  5. Barnard's test - Wikipedia

    en.wikipedia.org/wiki/Barnard's_test

    Under pressure from Fisher, Barnard retracted his test in a published paper, [8] however many researchers prefer Barnard’s exact test over Fisher's exact test for analyzing 2 × 2 contingency tables, [9] since its statistics are more powerful for the vast majority of experimental designs, whereas Fisher’s exact test statistics are conservative, meaning the significance shown by its p ...

  6. Omnibus test - Wikipedia

    en.wikipedia.org/wiki/Omnibus_test

    Tukey's HSD and Scheffé's procedure are one-step procedures and can be done without the omnibus F having to be significant. They are "a posteriori" tests, but in this case, "a posteriori" means "without prior knowledge", as in "without specific hypotheses." On the other hand, Fisher's Least Significant Difference test is a two-step procedure.

  7. Scoring algorithm - Wikipedia

    en.wikipedia.org/wiki/Scoring_algorithm

    Scoring algorithm, also known as Fisher's scoring, [1] is a form of Newton's method used in statistics to solve maximum likelihood equations numerically, ...

  8. Linear discriminant analysis - Wikipedia

    en.wikipedia.org/wiki/Linear_discriminant_analysis

    Linear discriminant analysis (LDA), normal discriminant analysis (NDA), canonical variates analysis (CVA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics and other fields, to find a linear combination of features that characterizes or separates two or more classes of objects or ...

  9. Boschloo's test - Wikipedia

    en.wikipedia.org/wiki/Boschloo's_test

    Fisher's exact test is a conditional test and appropriate for the first of the above mentioned cases. But if we treat the observed column sum s 1 {\displaystyle s_{1}} as fixed in advance, Fisher's exact test can also be applied to the second case.