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  2. Empirical probability - Wikipedia

    en.wikipedia.org/wiki/Empirical_probability

    In probability theory and statistics, the empirical probability, relative frequency, or experimental probability of an event is the ratio of the number of outcomes in which a specified event occurs to the total number of trials, [1] i.e. by means not of a theoretical sample space but of an actual experiment.

  3. Empirical measure - Wikipedia

    en.wikipedia.org/wiki/Empirical_measure

    In particular, the empirical measure of A is simply the empirical mean of the indicator function, P n (A) = P n I A. For a fixed measurable function f {\displaystyle f} , P n f {\displaystyle P_{n}f} is a random variable with mean E f {\displaystyle \mathbb {E} f} and variance 1 n E ( f − E f ) 2 {\displaystyle {\frac {1}{n}}\mathbb {E} (f ...

  4. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    In statistics, the 68–95–99.7 rule, also known as the empirical rule, and sometimes abbreviated 3sr, is a shorthand used to remember the percentage of values that lie within an interval estimate in a normal distribution: approximately 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.

  5. Glivenko–Cantelli theorem - Wikipedia

    en.wikipedia.org/wiki/Glivenko–Cantelli_theorem

    In the theory of probability, the Glivenko–Cantelli theorem (sometimes referred to as the Fundamental Theorem of Statistics), named after Valery Ivanovich Glivenko and Francesco Paolo Cantelli, describes the asymptotic behaviour of the empirical distribution function as the number of independent and identically distributed observations grows. [1]

  6. Sample mean and covariance - Wikipedia

    en.wikipedia.org/wiki/Sample_mean_and_covariance

    The sample mean and sample covariance are not robust statistics, meaning that they are sensitive to outliers. As robustness is often a desired trait, particularly in real-world applications, robust alternatives may prove desirable, notably quantile-based statistics such as the sample median for location, [4] and interquartile range (IQR) for ...

  7. Empirical process - Wikipedia

    en.wikipedia.org/wiki/Empirical_process

    In probability theory, an empirical process is a stochastic process that characterizes the deviation of the empirical distribution function from its expectation. In mean field theory , limit theorems (as the number of objects becomes large) are considered and generalise the central limit theorem for empirical measures .

  8. Empirical formula - Wikipedia

    en.wikipedia.org/wiki/Empirical_formula

    Glucose (C 6 H 12 O 6), ribose (C 5 H 10 O 5), Acetic acid (C 2 H 4 O 2), and formaldehyde (CH 2 O) all have different molecular formulas but the same empirical formula: CH 2 O.This is the actual molecular formula for formaldehyde, but acetic acid has double the number of atoms, ribose has five times the number of atoms, and glucose has six times the number of atoms.

  9. Statistical proof - Wikipedia

    en.wikipedia.org/wiki/Statistical_proof

    Bayesian statistics are based on a different philosophical approach for proof of inference.The mathematical formula for Bayes's theorem is: [|] = [|] [] []The formula is read as the probability of the parameter (or hypothesis =h, as used in the notation on axioms) “given” the data (or empirical observation), where the horizontal bar refers to "given".