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  2. Null distribution - Wikipedia

    en.wikipedia.org/wiki/Null_distribution

    Null distribution is a tool scientists often use when conducting experiments. The null distribution is the distribution of two sets of data under a null hypothesis. If the results of the two sets of data are not outside the parameters of the expected results, then the null hypothesis is said to be true. Null and alternative distribution

  3. Counternull - Wikipedia

    en.wikipedia.org/wiki/Counternull

    Thus the counternull is an alternative hypothesis that, when used to replace the null hypothesis, generates the same p-value as had the original null hypothesis of “no difference.” [3] Some researchers contend that reporting the counternull, in addition to the p -value, serves to counter two common errors of judgment: [ 4 ]

  4. Template : Classification of multiple hypothesis tests

    en.wikipedia.org/wiki/Template:Classification_of...

    The following table defines the possible outcomes when testing multiple null hypotheses. Suppose we have a number m of null hypotheses, denoted by: H 1, H 2, ..., H m. Using a statistical test, we reject the null hypothesis if the test is declared significant. We do not reject the null hypothesis if the test is non-significant.

  5. Alternative hypothesis - Wikipedia

    en.wikipedia.org/wiki/Alternative_hypothesis

    In statistical hypothesis testing, the alternative hypothesis is one of the proposed propositions in the hypothesis test. In general the goal of hypothesis test is to demonstrate that in the given condition, there is sufficient evidence supporting the credibility of alternative hypothesis instead of the exclusive proposition in the test (null hypothesis). [1]

  6. Bartlett's test - Wikipedia

    en.wikipedia.org/wiki/Bartlett's_test

    Thus, the null hypothesis is rejected if >, (where , is the upper tail critical value for the distribution). Bartlett's test is a modification of the corresponding likelihood ratio test designed to make the approximation to the χ k − 1 2 {\displaystyle \chi _{k-1}^{2}} distribution better (Bartlett, 1937).

  7. Fisher's method - Wikipedia

    en.wikipedia.org/wiki/Fisher's_method

    Fisher's method is typically applied to a collection of independent test statistics, usually from separate studies having the same null hypothesis. The meta-analysis null hypothesis is that all of the separate null hypotheses are true. The meta-analysis alternative hypothesis is that at least one of the separate alternative hypotheses is true.

  8. Portmanteau test - Wikipedia

    en.wikipedia.org/wiki/Portmanteau_test

    A portmanteau test is a type of statistical hypothesis test in which the null hypothesis is well specified, but the alternative hypothesis is more loosely specified. Tests constructed in this context can have the property of being at least moderately powerful against a wide range of departures from the null hypothesis.

  9. Wilks' theorem - Wikipedia

    en.wikipedia.org/wiki/Wilks'_theorem

    Where the null hypothesis represents a special case of the alternative hypothesis, the probability distribution of the test statistic is approximately a chi-squared distribution with degrees of freedom equal to , [2] respectively the number of free parameters of models alternative and null.