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  2. Sample mean and covariance - Wikipedia

    en.wikipedia.org/wiki/Sample_mean_and_covariance

    The arithmetic mean of a population, or population mean, is often denoted μ. [2] The sample mean ¯ (the arithmetic mean of a sample of values drawn from the population) makes a good estimator of the population mean, as its expected value is equal to the population mean (that is, it is an unbiased estimator).

  3. Expected value - Wikipedia

    en.wikipedia.org/wiki/Expected_value

    According to this definition, E[X] exists and is finite if and only if E[X +] and E[X −] are both finite. Due to the formula |X| = X + + X −, this is the case if and only if E|X| is finite, and this is equivalent to the absolute convergence conditions in the definitions above. As such, the present considerations do not define finite ...

  4. Mean - Wikipedia

    en.wikipedia.org/wiki/Mean

    The arithmetic mean of a set of numbers x 1, x 2, ..., x n is typically denoted using an overhead bar, ¯. [ note 1 ] If the numbers are from observing a sample of a larger group , the arithmetic mean is termed the sample mean ( x ¯ {\displaystyle {\bar {x}}} ) to distinguish it from the group mean (or expected value ) of the underlying ...

  5. Expected mean squares - Wikipedia

    en.wikipedia.org/wiki/Expected_mean_squares

    In statistics, expected mean squares (EMS) are the expected values of certain statistics arising in partitions of sums of squares in the analysis of variance (ANOVA). They can be used for ascertaining which statistic should appear in the denominator in an F-test for testing a null hypothesis that a particular effect is absent.

  6. Mean squared prediction error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_prediction_error

    First, with a data sample of length n, the data analyst may run the regression over only q of the data points (with q < n), holding back the other n – q data points with the specific purpose of using them to compute the estimated model’s MSPE out of sample (i.e., not using data that were used in the model estimation process).

  7. Post hoc analysis - Wikipedia

    en.wikipedia.org/wiki/Post_hoc_analysis

    In a scientific study, post hoc analysis (from Latin post hoc, "after this") consists of statistical analyses that were specified after the data were seen. [ 1 ] [ 2 ] They are usually used to uncover specific differences between three or more group means when an analysis of variance (ANOVA) test is significant. [ 3 ]

  8. Completeness (statistics) - Wikipedia

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

    The Bernoulli model admits a complete statistic. [1] Let X be a random sample of size n such that each X i has the same Bernoulli distribution with parameter p. Let T be the number of 1s observed in the sample, i.e. = =. T is a statistic of X which has a binomial distribution with parameters (n,p).

  9. Regression toward the mean - Wikipedia

    en.wikipedia.org/wiki/Regression_toward_the_mean

    Galton's experimental setup "Standard eugenics scheme of descent" – early application of Galton's insight [1]. In statistics, regression toward the mean (also called regression to the mean, reversion to the mean, and reversion to mediocrity) is the phenomenon where if one sample of a random variable is extreme, the next sampling of the same random variable is likely to be closer to its mean.