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  2. Bernoulli number - Wikipedia

    en.wikipedia.org/wiki/Bernoulli_number

    In mathematics, the Bernoulli numbers B n are a sequence of rational numbers which occur frequently in analysis.The Bernoulli numbers appear in (and can be defined by) the Taylor series expansions of the tangent and hyperbolic tangent functions, in Faulhaber's formula for the sum of m-th powers of the first n positive integers, in the Euler–Maclaurin formula, and in expressions for certain ...

  3. Pairwise independence - Wikipedia

    en.wikipedia.org/wiki/Pairwise_independence

    Bounds on the probability that the sum of Bernoulli random variables is at least one, commonly known as the union bound, are provided by the Boole–Fréchet [4] [5] inequalities. While these bounds assume only univariate information, several bounds with knowledge of general bivariate probabilities, have been proposed too.

  4. Bernoulli distribution - Wikipedia

    en.wikipedia.org/wiki/Bernoulli_distribution

    The categorical distribution is the generalization of the Bernoulli distribution for variables with any constant number of discrete values. The Beta distribution is the conjugate prior of the Bernoulli distribution. [5] The geometric distribution models the number of independent and identical Bernoulli trials needed to get one success.

  5. Relationships among probability distributions - Wikipedia

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

    Other distributions are not closed under convolution, but their sum has a known distribution: The sum of n Bernoulli (p) random variables is a binomial (n, p) random variable. The sum of n geometric random variables with probability of success p is a negative binomial random variable with parameters n and p.

  6. Binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Binomial_distribution

    A Binomial distributed random variable X ~ B(n, p) can be considered as the sum of n Bernoulli distributed random variables. So the sum of two Binomial distributed random variables X ~ B(n, p) and Y ~ B(m, p) is equivalent to the sum of n + m Bernoulli distributed random variables, which means Z = X + Y ~ B(n + m, p). This can also be proven ...

  7. Note G - Wikipedia

    en.wikipedia.org/wiki/Note_G

    The third column tells the computer exactly what command is taking place, (For example, on line 1, the command performed is "" - the first iteration of variable 2 is multiplied by the first iteration of variable 3.) and only incorporates one operation between two terms per line. Column 4 - "Variables receiving results" takes note of where the ...

  8. Categorical distribution - Wikipedia

    en.wikipedia.org/wiki/Categorical_distribution

    The crucial line above is the third. The second follows directly from the definition of expected value. The third line is particular to the categorical distribution, and follows from the fact that, in the categorical distribution specifically, the expected value of seeing a particular value i is directly specified by the associated parameter p ...

  9. Summation - Wikipedia

    en.wikipedia.org/wiki/Summation

    In mathematics, summation is the addition of a sequence of numbers, called addends or summands; the result is their sum or total.Beside numbers, other types of values can be summed as well: functions, vectors, matrices, polynomials and, in general, elements of any type of mathematical objects on which an operation denoted "+" is defined.