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Hochberg's procedure is more powerful than Holm's. Nevertheless, while Holm’s is a closed testing procedure (and thus, like Bonferroni, has no restriction on the joint distribution of the test statistics), Hochberg’s is based on the Simes test, so it holds only under non-negative dependence.
@Halcyon0612: If you reply to other users on your talk page, it is good practice to inform them about the reply on their talk page by using the talkback template. Just place {} on their talk page to let them know you replied to them on your talk page. Vanjagenije 23:02, 30 January 2015 (UTC)
The purpose of this page is to centralize information about reliable sources for use by new page reviewers when reviewing new articles. It is intended as a supplement to the reliable sources noticeboard and perennial sources list, to help page reviewers unfamiliar with a given subject assess notability and neutrality of an article––entries should focus on whether a specific publication is ...
In statistics, data can have any of various types. Statistical data types include categorical (e.g. country), directional (angles or directions, e.g. wind measurements), count (a whole number of events), or real intervals (e.g. measures of temperature).
Though there are many approximate solutions (such as Welch's t-test), the problem continues to attract attention [4] as one of the classic problems in statistics. Multiple comparisons: There are various ways to adjust p-values to compensate for the simultaneous or sequential testing of hypotheses. Of particular interest is how to simultaneously ...
In its second quarter results, revenue increased 82% year over year to $954.7 million, soaring past Wall Street estimates of $751.5 million.. Net income for the quarter also came in higher at $219 ...
Cohen's kappa measures the agreement between two raters who each classify N items into C mutually exclusive categories. The definition of is =, where p o is the relative observed agreement among raters, and p e is the hypothetical probability of chance agreement, using the observed data to calculate the probabilities of each observer randomly selecting each category.
In practice, testing measures are never perfectly consistent. Theories of test reliability have been developed to estimate the effects of inconsistency on the accuracy of measurement. The basic starting point for almost all theories of test reliability is the idea that test scores reflect the influence of two sorts of factors: [ 7 ]