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Distribution (number theory) – function on finite sets which is analogous to an integralPages displaying wikidata descriptions as a fallback. Distribution on a linear algebraic group – Linear function satisfying a support condition. Green's function – Impulse response of an inhomogeneous linear differential operator.
In mathematics, the distributive property of binary operations is a generalization of the distributive law, which asserts that the equality. is always true in elementary algebra . For example, in elementary arithmetic, one has Therefore, one would say that multiplication distributes over addition . This basic property of numbers is part of the ...
An expectation E on an algebra A of random variables is a normalized, positive linear functional. What this means is that E[k] = k where k is a constant; E[X * X] ≥ 0 for all random variables X; E[X + Y] = E[X] + E[Y] for all random variables X and Y; and; E[kX] = kE[X] if k is a constant. One may generalize this setup, allowing the algebra ...
In statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is. The parameter is the mean or expectation of the distribution (and also its median and mode ), while the parameter is its standard deviation.
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 ...
Probability density functions (pdfs) and probability mass functions are denoted by lowercase letters, e.g. , or . Cumulative distribution functions (cdfs) are denoted by uppercase letters, e.g. , or . In particular, the pdf of the standard normal distribution is denoted by , and its cdf by .
Central limit theorem. In probability theory, the central limit theorem ( CLT) states that, under appropriate conditions, the distribution of a normalized version of the sample mean converges to a standard normal distribution. This holds even if the original variables themselves are not normally distributed.
the normal cumulative distribution function plotted in the complex ... the header math.h shall declare and the mathematical library libm shall provide the functions ...
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