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Its test statistic follows the F-distribution with (n - 1, m - 1)-degrees of freedom, where n and m are the respective sample sizes.ĪNOVA is used to test the equality of means in three or more groups that come from normally distributed populations with equal variances. All of them are right-tailed tests.Ī test for the equality of variances in two normally distributed populations. Two-tailed test: p-value = 2 * min we denote the smaller of the numbers a and b.)īelow we list the most important tests that produce F-scores. Right-tailed test: p-value = Pr(S ≥ x | H 0) Left-tailed test: p-value = Pr(S ≤ x | H 0) In formulas below, S stands for a test statistic, x for the value it produced for a given sample, and Pr(event | H 0) is the probability of an event, calculated under the assumption that H 0 is true:
![hypothesis test calculator p value hypothesis test calculator p value](https://cdn.educba.com/academy/wp-content/uploads/2019/03/P-Value-in-excel-1.png)
It is the alternative hypothesis which determines what "extreme" actually means, so the p-value depends on the alternative hypothesis that you state: left-tailed, right-tailed, or two-tailed. More intuitively, p-value answers the question:Īssuming that I live in a world where the null hypothesis holds, how probable is it that, for another sample, the test I'm performing will generate a value at least as extreme as the one I observed for the sample I already have? It is crucial to remember that this probability is calculated under the assumption that the null hypothesis is true!
![hypothesis test calculator p value hypothesis test calculator p value](https://getcalc.com/formula/statistics/zstatistic-significance-test-two-proportions-difference-known-pvalues.png)
Formally, the p-value is the probability that the test statistic will produce values at least as extreme as the value it produced for your sample.