The Bernoulli distribution, named after the Swiss mathematician Jacob Bernoulli, is the discrete probability distribution of a random variable that takes the value 1 with probability p and the value 0 with probability q equal to 1 minus p. Informally, it models the outcome of any single yes-or-no experiment, producing a boolean-valued result that represents success or failure at a fixed probability. It is the simplest building block of discrete probability theory and underlies more complex distributions such as the binomial.
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In probability theory and statistics, the Bernoulli distribution, named after Swiss mathematician Jacob Bernoulli, is the discrete probability distribution of a random variable which takes the value 1 with probability p {\displaystyle p} and the value 0 with probability q = 1 − p {\displaystyle q=1-p} . Less formally, it can be thought of as a model for the set of possible outcomes of any single experiment that asks a yes-no question.
Principal Result Of: Jacob Bernoulli, Lead sentence of the article on the result
In probability theory and statistics, the Bernoulli distribution, named after Swiss mathematician Jacob Bernoulli, is the discrete probability distribution of a random variable which takes the value 1 with probability p {\displaystyle p} and the value 0 with probability q = 1 − p {\displaystyle q=1-p} .
In Branch: Probability and Statistics, Lead sentence
In probability theory and statistics, the Bernoulli distribution, named after Swiss mathematician Jacob Bernoulli, is the discrete
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