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Statistical significance. In statistical hypothesis testing, [1] [2] a result has statistical significance when a result at least as "extreme" would be very infrequent if the null hypothesis were true. [3] More precisely, a study's defined significance level, denoted by , is the probability of the study rejecting the null hypothesis, given that ...
Student's t-test is a statistical test used to test whether the difference between the response of two groups is statistically significant or not. It is any statistical 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 would follow a ...
Power of a test. In statistics, the power of a binary hypothesis test is the probability that the test correctly rejects the null hypothesis ( ) when a specific alternative hypothesis ( ) is true. It is commonly denoted by , and represents the chances of a true positive detection conditional on the actual existence of an effect to detect.
Statistical hypothesis testing is considered a mature area within statistics, but a limited amount of development continues. An academic study states that the cookbook method of teaching introductory statistics leaves no time for history, philosophy or controversy. Hypothesis testing has been taught as received unified method.
In broad usage, the "practical clinical significance" answers the question, how effective is the intervention or treatment, or how much change does the treatment cause. In terms of testing clinical treatments, practical significance optimally yields quantified information about the importance of a finding, using metrics such as effect size, number needed to treat (NNT), and preventive fraction.
Statistics is a mathematical body of science that pertains to the collection, analysis, interpretation or explanation, and presentation of data, [9] or as a branch of mathematics. [10] Some consider statistics to be a distinct mathematical science rather than a branch of mathematics. While many scientific investigations make use of data ...
The p -value is used in the context of null hypothesis testing in order to quantify the statistical significance of a result, the result being the observed value of the chosen statistic . [note 2] The lower the p -value is, the lower the probability of getting that result if the null hypothesis were true. A result is said to be statistically ...
Meta-analysis is the statistical combination of the results of multiple studies addressing a similar research question. An important part of this method involves computing an effect size across all of the studies; this involves extracting effect sizes and variance measures from various studies.