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  2. Convolution of probability distributions - Wikipedia

    en.wikipedia.org/wiki/Convolution_of_probability...

    The probability distribution of the sum of two or more independent random variables is the convolution of their individual distributions. The term is motivated by the fact that the probability mass function or probability density function of a sum of independent random variables is the convolution of their corresponding probability mass functions or probability density functions respectively.

  3. Weibull distribution - Wikipedia

    en.wikipedia.org/wiki/Weibull_distribution

    In probability theory and statistics, the Weibull distribution / ˈ w aɪ b ʊ l / 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.

  4. Relationships among probability distributions - Wikipedia

    en.wikipedia.org/wiki/Relationships_among...

    The product of independent random variables X and Y may belong to the same family of distribution as X and Y: Bernoulli distribution and log-normal distribution. Example: If X 1 and X 2 are independent log-normal random variables with parameters (μ 1, σ 2 1) and (μ 2, σ 2 2) respectively, then X 1 X 2 is a log-normal random variable with ...

  5. Illustration of the central limit theorem - Wikipedia

    en.wikipedia.org/wiki/Illustration_of_the...

    Both involve the sum of independent and identically-distributed random variables and show how the probability distribution of the sum approaches the normal distribution as the number of terms in the sum increases. The first illustration involves a continuous probability distribution, for which the random variables have a probability density ...

  6. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The Bernoulli distribution, which takes value 1 with probability p and value 0 with probability q = 1 − p. The Rademacher distribution, which takes value 1 with probability 1/2 and value −1 with probability 1/2. The binomial distribution, which describes the number of successes in a series of independent Yes/No experiments all with the same ...

  7. Mixture distribution - Wikipedia

    en.wikipedia.org/wiki/Mixture_distribution

    That is, for each value of a in some set A, p(x;a) is a probability density function with respect to x. Given a probability density function w (meaning that w is nonnegative and integrates to 1), the function = (;) is again a probability density function for x. A similar integral can be written for the cumulative distribution function.

  8. Ex-Abercrombie & Fitch CEO has dementia, lawyers say - AOL

    www.aol.com/ex-abercrombie-fitch-ceo-dementia...

    The former CEO of Abercrombie & Fitch (A&F) has dementia and late onset Alzheimer's disease, his legal team has said in a court document filed in New York. Lawyers for Mike Jeffries have requested ...

  9. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    For instance, if X is used to denote the outcome of a coin toss ("the experiment"), then the probability distribution of X would take the value 0.5 (1 in 2 or 1/2) for X = heads, and 0.5 for X = tails (assuming that the coin is fair). More commonly, probability distributions are used to compare the relative occurrence of many different random ...