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  2. Student's t-test - Wikipedia

    en.wikipedia.org/wiki/Student's_t-test

    From the t-test, the difference between the group means is 6-2=4. From the regression, the slope is also 4 indicating that a 1-unit change in drug dose (from 0 to 1) gives a 4-unit change in mean word recall (from 2 to 6). The t-test p-value for the difference in means, and the regression p-value for the slope, are both 0.00805. The methods ...

  3. Duncan's new multiple range test - Wikipedia

    en.wikipedia.org/wiki/Duncan's_new_multiple_range...

    The new multiple range test proposed by Duncan makes use of special protection levels based upon degrees of freedom.Let , = be the protection level for testing the significance of a difference between two means; that is, the probability that a significant difference between two means will not be found if the population means are equal.

  4. Compact letter display - Wikipedia

    en.wikipedia.org/wiki/Compact_letter_display

    The Tukey's range test uncovered that San Francisco & Spokane did not have statistically different rainfall mean (at the alpha = 0.05 level) with a p-value of 0.08. Seattle & Portland also did not have statistically different rainfall mean, with a difference associated with a p-value of 0.54.

  5. Student's t-distribution - Wikipedia

    en.wikipedia.org/wiki/Student's_t-distribution

    The Student's t distribution plays a role in a number of widely used statistical analyses, including Student's t test for assessing the statistical significance of the difference between two sample means, the construction of confidence intervals for the difference between two population means, and in linear regression analysis.

  6. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    Compute from the observations the observed value t obs of the test statistic T. Decide to either reject the null hypothesis in favor of the alternative or not reject it. The Neyman-Pearson decision rule is to reject the null hypothesis H 0 if the observed value t obs is in the critical region, and not to reject the null hypothesis otherwise. [31]

  7. Behrens–Fisher problem - Wikipedia

    en.wikipedia.org/wiki/Behrens–Fisher_problem

    In statistics, the Behrens–Fisher problem, named after Walter-Ulrich Behrens and Ronald Fisher, is the problem of interval estimation and hypothesis testing concerning the difference between the means of two normally distributed populations when the variances of the two populations are not assumed to be equal, based on two independent samples.

  8. Permutation test - Wikipedia

    en.wikipedia.org/wiki/Permutation_test

    The permutation test is designed to determine whether the observed difference between the sample means is large enough to reject, at some significance level, the null hypothesis H that the data drawn from is from the same distribution as the data drawn from . The test proceeds as follows.

  9. Test statistic - Wikipedia

    en.wikipedia.org/wiki/Test_statistic

    If there is interest in the marginal probability of obtaining a tail, only the number T out of the 100 flips that produced a tail needs to be recorded. But T can also be used as a test statistic in one of two ways: the exact sampling distribution of T under the null hypothesis is the binomial distribution with parameters 0.5 and 100.