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  2. Order statistic - Wikipedia

    en.wikipedia.org/wiki/Order_statistic

    Order statistic. Probability density functions of the order statistics for a sample of size n = 5 from an exponential distribution with unit scale parameter. In statistics, the k th order statistic of a statistical sample is equal to its k th-smallest value. [1] Together with rank statistics, order statistics are among the most fundamental ...

  3. Simpson's paradox - Wikipedia

    en.wikipedia.org/wiki/Simpson's_paradox

    Simpson's paradox is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined. This result is often encountered in social-science and medical-science statistics, [1][2][3] and is particularly problematic when frequency data are unduly given causal ...

  4. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    Statistics (from German: Statistik, orig. "description of a state, a country") [1][2] is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. [3][4][5] In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a ...

  5. Stochastic process - Wikipedia

    en.wikipedia.org/wiki/Stochastic_process

    Introduction. A stochastic or random process can be defined as a collection of random variables that is indexed by some mathematical set, meaning that each random variable of the stochastic process is uniquely associated with an element in the set. [4][5] The set used to index the random variables is called the index set.

  6. Moment-generating function - Wikipedia

    en.wikipedia.org/wiki/Moment-generating_function

    In probability theory and statistics, the moment-generating function of a real-valued random variable is an alternative specification of its probability distribution. Thus, it provides the basis of an alternative route to analytical results compared with working directly with probability density functions or cumulative distribution functions.

  7. Extreme value theory - Wikipedia

    en.wikipedia.org/wiki/Extreme_value_theory

    Extreme value theory or extreme value analysis (EVA) is the study of extremes in statistical distributions. It is widely used in many disciplines, such as structural engineering, finance, economics, earth sciences, traffic prediction, and geological engineering. For example, EVA might be used in the field of hydrology to estimate the ...

  8. Weibull distribution - Wikipedia

    en.wikipedia.org/wiki/Weibull_distribution

    In probability theory and statistics, the Weibull distribution / ˈwaɪbʊl / is a continuous probability distribution. It models a broad range of random variables, largely in the nature of a time to failure or time between events. Examples are maximum one-day rainfalls and the time a user spends on a web page.

  9. Law of averages - Wikipedia

    en.wikipedia.org/wiki/Law_of_averages

    As invoked in everyday life, the "law" usually reflects wishful thinking or a poor understanding of statistics rather than any mathematical principle. While there is a real theorem that a random variable will reflect its underlying probability over a very large sample, the law of averages typically assumes that an unnatural short-term "balance ...