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  2. Orders of magnitude (probability) - Wikipedia

    en.wikipedia.org/wiki/Orders_of_magnitude...

    2.1×10 −2: Probability of being dealt a three of a kind in poker 2.3×10 −2: Gaussian distribution: probability of a value being more than 2 standard deviations from the mean on a specific side [17] 2.7×10 −2: Probability of winning any prize in the Powerball with one ticket in 2006 3.3×10 −2: Probability of a human giving birth to ...

  3. Logarithmic distribution - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_distribution

    This leads directly to the probability mass function of a Log(p)-distributed random variable: = ⁡ for k ≥ 1, and where 0 < p < 1. Because of the identity above, the distribution is properly normalized. The cumulative distribution function is

  4. Wikipedia:WikiProject Statistics - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:WikiProject...

    Suggestions regarding the structure of articles about probability distributions are here; Include either of these infoboxes (feel free to leave some parameters blank): {{Infobox probability distribution}} (e.g., Negative binomial distribution) {{Infobox probability distribution 2}} (e.g., Geometric distribution)

  5. Outline of probability - Wikipedia

    en.wikipedia.org/wiki/Outline_of_probability

    The certainty that is adopted can be described in terms of a numerical measure, and this number, between 0 and 1 (where 0 indicates impossibility and 1 indicates certainty) is called the probability. Probability theory is used extensively in statistics , mathematics , science and philosophy to draw conclusions about the likelihood of potential ...

  6. Taylor expansions for the moments of functions of random ...

    en.wikipedia.org/wiki/Taylor_expansions_for_the...

    In probability theory, it is possible to approximate the moments of a function f of a random variable X using Taylor expansions, provided that f is sufficiently differentiable and that the moments of X are finite. A simulation-based alternative to this approximation is the application of Monte Carlo simulations.

  7. Turning point test - Wikipedia

    en.wikipedia.org/wiki/Turning_point_test

    In statistical hypothesis testing, a turning point test is a statistical test of the independence of a series of random variables. [1] [2] [3] Maurice Kendall and Alan Stuart describe the test as "reasonable for a test against cyclicity but poor as a test against trend." [4] [5] The test was first published by Irénée-Jules Bienaymé in 1874 ...

  8. Kolmogorov's three-series theorem - Wikipedia

    en.wikipedia.org/wiki/Kolmogorov's_three-series...

    In probability theory, Kolmogorov's Three-Series Theorem, named after Andrey Kolmogorov, gives a criterion for the almost sure convergence of an infinite series of random variables in terms of the convergence of three different series involving properties of their probability distributions.

  9. Law of truly large numbers - Wikipedia

    en.wikipedia.org/wiki/Law_of_truly_large_numbers

    For an event X that occurs with very low probability of 0.0000001%, or once in one billion trials, in any single sample (see also almost never), considering 1,000,000,000 as a "truly large" number of independent samples gives the probability of occurrence of X equal to 1 − 0.999999999 1000000000 ≈ 0.63 = 63% and a number of independent ...

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