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  2. Notation in probability and statistics - Wikipedia

    en.wikipedia.org/wiki/Notation_in_probability...

    The probability is sometimes written to distinguish it from other functions and measure P to avoid having to define "P is a probability" and () is short for ({: ()}), where is the event space, is a random variable that is a function of (i.e., it depends upon ), and is some outcome of interest within the domain specified by (say, a particular ...

  3. 68–95–99.7 rule - Wikipedia

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

    The "68–95–99.7 rule" is often used to quickly get a rough probability estimate of something, given its standard deviation, if the population is assumed to be normal. It is also used as a simple test for outliers if the population is assumed normal, and as a normality test if the population is potentially not normal.

  4. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    A probability distribution is a mathematical description of the probabilities of events, subsets of the sample space. The sample space, often represented in notation by , is the set of all possible outcomes of a random phenomenon being observed.

  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. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    Let be a discrete random variable with probability mass function depending on a parameter .Then the function = = (=),considered as a function of , is the likelihood function, given the outcome of the random variable .

  7. Beta distribution - Wikipedia

    en.wikipedia.org/wiki/Beta_distribution

    In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval [0, 1] or (0, 1) in terms of two positive parameters, denoted by alpha (α) and beta (β), that appear as exponents of the variable and its complement to 1, respectively, and control the shape of the distribution.

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