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  2. Method of moments (statistics) - Wikipedia

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

    In statistics, the method of moments is a method of estimation of population parameters.The same principle is used to derive higher moments like skewness and kurtosis.. It starts by expressing the population moments (i.e., the expected values of powers of the random variable under consideration) as functions of the parameters of interest.

  3. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    One approach that does yield an interval that can be interpreted as having a given probability of containing the true value is to use a credible interval from Bayesian statistics: this approach depends on a different way of interpreting what is meant by "probability", that is as a Bayesian probability.

  4. Probability theory - Wikipedia

    en.wikipedia.org/wiki/Probability_theory

    Probability theory or probability calculus is the branch of mathematics concerned with probability.Although there are several different probability interpretations, probability theory treats the concept in a rigorous mathematical manner by expressing it through a set of axioms.

  5. 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 or 3 σ, 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 ...

  6. Order statistic - Wikipedia

    en.wikipedia.org/wiki/Order_statistic

    Order statistics have a lot of applications in areas as reliability theory, financial mathematics, survival analysis, epidemiology, sports, quality control, actuarial risk, etc. There is an extensive literature devoted to studies on applications of order statistics in these fields.

  7. Statistical model - Wikipedia

    en.wikipedia.org/wiki/Statistical_model

    In Bayesian statistics, the model is extended by adding a probability distribution over the parameter space . A statistical model can sometimes distinguish two sets of probability distributions. The first set Q = { F θ : θ ∈ Θ } {\displaystyle {\mathcal {Q}}=\{F_{\theta }:\theta \in \Theta \}} is the set of models considered for inference.

  8. Survey sampling - Wikipedia

    en.wikipedia.org/wiki/Survey_sampling

    The elementary book by Scheaffer et alia uses quadratic equations from high-school algebra: Scheaffer, Richard L., William Mendenhal and R. Lyman Ott. Elementary survey sampling, Fifth Edition. Belmont: Duxbury Press, 1996. More mathematical statistics is required for Lohr, for Särndal et alia, and for Cochran (classic): Cochran, William G ...

  9. Covariance matrix - Wikipedia

    en.wikipedia.org/wiki/Covariance_matrix

    Throughout this article, boldfaced unsubscripted and are used to refer to random vectors, and Roman subscripted and are used to refer to scalar random variables.. If the entries in the column vector = (,, …,) are random variables, each with finite variance and expected value, then the covariance matrix is the matrix whose (,) entry is the covariance [1]: 177 ...

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