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  2. t-statistic - Wikipedia

    en.wikipedia.org/wiki/T-statistic

    Most frequently, t statistics are used in Student's t-tests, a form of statistical hypothesis testing, and in the computation of certain confidence intervals. The key property of the t statistic is that it is a pivotal quantity – while defined in terms of the sample mean, its sampling distribution does not depend on the population parameters, and thus it can be used regardless of what these ...

  3. Student's t-distribution - Wikipedia

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

    The following table lists values for t distributions with ν degrees of freedom for a range of one-sided or two-sided critical regions. The first column is ν , the percentages along the top are confidence levels α , {\displaystyle \ \alpha \ ,} and the numbers in the body of the table are the t α , n − 1 {\displaystyle t_{\alpha ,n-1 ...

  4. Student's t-test - Wikipedia

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

    The t-test p-value for the difference in means, and the regression p-value for the slope, are both 0.00805. The methods give identical results. This example shows that, for the special case of a simple linear regression where there is a single x-variable that has values 0 and 1, the t-test gives the same results as the linear regression. The ...

  5. Critical value - Wikipedia

    en.wikipedia.org/wiki/Critical_value

    Critical value or threshold value can refer to: A quantitative threshold in medicine, chemistry and physics; Critical value (statistics), boundary of the acceptance region while testing a statistical hypothesis; Value of a function at a critical point (mathematics) Critical point (thermodynamics) of a statistical system.

  6. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    Critical value s of a statistical test are the boundaries of the acceptance region of the test. [41] The acceptance region is the set of values of the test statistic for which the null hypothesis is not rejected. Depending on the shape of the acceptance region, there can be one or more than one critical value.

  7. One- and two-tailed tests - Wikipedia

    en.wikipedia.org/wiki/One-_and_two-tailed_tests

    The statistical tables for t and for Z provide critical values for both one- and two-tailed tests. That is, they provide the critical values that cut off an entire region at one or the other end of the sampling distribution as well as the critical values that cut off the regions (of half the size) at both ends of the sampling distribution.

  8. Hotelling's T-squared distribution - Wikipedia

    en.wikipedia.org/wiki/Hotelling's_T-squared...

    In statistics, particularly in hypothesis testing, the Hotelling's T-squared distribution (T 2), proposed by Harold Hotelling, [1] is a multivariate probability distribution that is tightly related to the F-distribution and is most notable for arising as the distribution of a set of sample statistics that are natural generalizations of the statistics underlying the Student's t-distribution.

  9. Augmented Dickey–Fuller test - Wikipedia

    en.wikipedia.org/wiki/Augmented_Dickey–Fuller_test

    This is more negative than the tabulated critical value of −3.50, so at the 95% level, the null hypothesis of a unit root will be rejected. Critical values for Dickey–Fuller t -distribution. Without trend