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  2. Pivotal quantity - Wikipedia

    en.wikipedia.org/wiki/Pivotal_quantity

    Then is called a pivotal quantity (or simply a pivot). Pivotal quantities are commonly used for normalization to allow data from different data sets to be compared. It is relatively easy to construct pivots for location and scale parameters: for the former we form differences so that location cancels, for the latter ratios so that scale cancels.

  3. Ancillary statistic - Wikipedia

    en.wikipedia.org/wiki/Ancillary_statistic

    Conversely, given i.i.d. normal variables with known mean 1 and unknown variance σ 2, the sample mean ¯ is not an ancillary statistic of the variance, as the sampling distribution of the sample mean is N(1, σ 2 /n), which does depend on σ 2 – this measure of location (specifically, its standard error) depends on dispersion.

  4. Fisher information - Wikipedia

    en.wikipedia.org/wiki/Fisher_information

    The Fisher information is a way of measuring the amount of information that an observable random variable carries about an unknown parameter upon which the probability of depends.

  5. Likelihood-ratio test - Wikipedia

    en.wikipedia.org/wiki/Likelihood-ratio_test

    The likelihood-ratio test, also known as Wilks test, [2] is the oldest of the three classical approaches to hypothesis testing, together with the Lagrange multiplier test and the Wald test. [3] In fact, the latter two can be conceptualized as approximations to the likelihood-ratio test, and are asymptotically equivalent.

  6. Cumulant - Wikipedia

    en.wikipedia.org/wiki/Cumulant

    The cumulants are κ 1 = μ, κ 2 = σ 2, and κ 3 = κ 4 = ⋅⋅⋅ = 0. The special case σ 2 = 0 is a constant random variable X = μ. The cumulants of the uniform distribution on the interval [−1, 0] are κ n = B n /n, where B n is the n th Bernoulli number. The cumulants of the exponential distribution with rate parameter λ are κ n ...

  7. Student's t-distribution - Wikipedia

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

    In other words, 90% of the times that a lower threshold is calculated by this method from particular samples, this lower threshold lies below the true mean. So that at 80% confidence (calculated from 100% − 2 × (1 − 90%) = 80%), we have a true mean lying within the interval

  8. Bootstrapping (statistics) - Wikipedia

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

    The bootstrap sample is taken from the original by using sampling with replacement (e.g. we might 'resample' 5 times from [1,2,3,4,5] and get [2,5,4,4,1]), so, assuming N is sufficiently large, for all practical purposes there is virtually zero probability that it will be identical to the original "real" sample. This process is repeated a large ...

  9. Common Core - Wikipedia

    en.wikipedia.org/wiki/Common_Core

    The Common Core State Standards Initiative, also known as simply Common Core, was an American, multi-state educational initiative begun in 2010 with the goal of increasing consistency across state standards, or what K–12 students throughout the United States should know in English language arts and mathematics at the conclusion of each school grade.

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