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One may report that the left or right tail probability as the one-tailed p-value, which ultimately corresponds to the direction in which the test statistic deviates from H 0. [3] In a two-tailed test, "extreme" means "either sufficiently small or sufficiently large", and values in either direction are considered significant. [ 4 ]
How to perform a Z test when T is a statistic that is approximately normally distributed under the null hypothesis is as follows: First, estimate the expected value μ of T under the null hypothesis, and obtain an estimate s of the standard deviation of T. Second, determine the properties of T : one tailed or two tailed.
A one-sample Student's t-test is a location test of whether the mean of a population has a value specified in a null hypothesis. In testing the null hypothesis that the population mean is equal to a specified value μ 0 , one uses the statistic
If we use the test statistic /, then under the null hypothesis is exactly 1 for two-sided p-value, and exactly / for one-sided left-tail p-value, and same for one-sided right-tail p-value. If we consider every outcome that has equal or lower probability than "3 heads 3 tails" as "at least as extreme", then the p -value is exactly 1 / 2 ...
The p-value is the probability that a test statistic which is at least as extreme as the one obtained would occur under the null hypothesis. At a significance level of 0.05, a fair coin would be expected to (incorrectly) reject the null hypothesis (that it is fair) in 1 out of 20 tests on average.
A one-tailed hypothesis (tested using a one-sided test) [2] is an inexact hypothesis in which the value of a parameter is specified as being either: above or equal to a certain value, or; below or equal to a certain value. A one-tailed hypothesis is said to have directionality. Fisher's original (lady tasting tea) example was a one-tailed test ...
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Fisher's exact 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.