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  2. p-value - Wikipedia

    en.wikipedia.org/wiki/P-value

    In 2016, the American Statistical Association (ASA) made a formal statement that "p-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone" and that "a p-value, or statistical significance, does not measure the size of an effect or the importance of a ...

  3. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    In standard cases this will be a well-known result. For example, the test statistic might follow a Student's t distribution with known degrees of freedom, or a normal distribution with known mean and variance. Select a significance level (α), the maximum acceptable false positive rate. Common values are 5% and 1%.

  4. Pearson's chi-squared test - Wikipedia

    en.wikipedia.org/wiki/Pearson's_chi-squared_test

    For the test of independence, also known as the test of homogeneity, a chi-squared probability of less than or equal to 0.05 (or the chi-squared statistic being at or larger than the 0.05 critical point) is commonly interpreted by applied workers as justification for rejecting the null hypothesis that the row variable is independent of the ...

  5. Effect size - Wikipedia

    en.wikipedia.org/wiki/Effect_size

    In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...

  6. Statistical significance - Wikipedia

    en.wikipedia.org/wiki/Statistical_significance

    The article "Earliest Known Uses of Some of the Words of Mathematics (S)" contains an entry on Significance that provides some historical information. " The Concept of Statistical Significance Testing Archived 2022-09-07 at the Wayback Machine " (February 1994): article by Bruce Thompon hosted by the ERIC Clearinghouse on Assessment and ...

  7. Power (statistics) - Wikipedia

    en.wikipedia.org/wiki/Power_(statistics)

    If we wish to reject the null at significance level =, we must find the critical value such that the probability of > under the null is equal to . If n is large, the t-distribution converges to the standard normal distribution (thus no longer involving n ) and so through use of the corresponding quantile function Φ − 1 {\displaystyle \Phi ...

  8. Chi-squared distribution - Wikipedia

    en.wikipedia.org/wiki/Chi-squared_distribution

    These values can be calculated evaluating the quantile function (also known as "inverse CDF" or "ICDF") of the chi-squared distribution; [23] e. g., the χ 2 ICDF for p = 0.05 and df = 7 yields 2.1673 ≈ 2.17 as in the table above, noticing that 1 – p is the p-value from the table.

  9. Z-test - Wikipedia

    en.wikipedia.org/wiki/Z-test

    Z-test tests the mean of a distribution. For each significance level in the confidence interval, the Z-test has a single critical value (for example, 1.96 for 5% two tailed) which makes it more convenient than the Student's t-test whose critical values are defined by the sample size (through the corresponding degrees of freedom). Both the Z ...