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The term significance does not imply importance here, and the term statistical significance is not the same as research significance, theoretical significance, or practical significance. [1] [2] [18] [19] For example, the term clinical significance refers to the practical importance of a treatment effect. [20]
For a given significance level in a two-tailed test for a test statistic, the corresponding one-tailed tests for the same test statistic will be considered either twice as significant (half the p-value) if the data is in the direction specified by the test, or not significant at all (p-value above ) if the data is in the direction opposite of ...
This q s test statistic can then be compared to a q value for the chosen significance level α from a table of the studentized range distribution. If the q s value is larger than the critical value q α obtained from the distribution, the two means are said to be significantly different at level α : 0 ≤ α ≤ 1 . {\displaystyle \ \alpha ...
[4] [14] [15] [16] The apparent contradiction stems from the combination of a discrete statistic with fixed significance levels. [17] [18] Consider the following proposal for a significance test at the 5%-level: reject the null hypothesis for each table to which Fisher's test assigns a p-value equal to or smaller than 5%. Because the set of all ...
An example of Neyman–Pearson hypothesis testing (or null hypothesis statistical significance testing) can be made by a change to the radioactive suitcase example. If the "suitcase" is actually a shielded container for the transportation of radioactive material, then a test might be used to select among three hypotheses: no radioactive source ...
In the trivial case of zero effect size, power is at a minimum and equal to the significance level of the test , in this example 0.05. For finite sample sizes and non-zero variability, it is the case here, as is typical, that power cannot be made equal to 1 except in the trivial case where α = 1 {\displaystyle \alpha =1} so the null is always ...
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The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]