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mathematical physics > special function > normal distribution

mathematical analysis > functional analysis > special function > normal distribution

probability theory > probability distribution > normal distribution

mathematical statistics > probability distribution > normal distribution

Preferred term

normal distribution

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

${\\displaystyle f(x)={\ rac {1}{\\sigma {\\sqrt {2\\pi }}}}e^{-{\ rac {1}{2}}\\left({\ rac {x-\\mu }{\\sigma }}\ ight)^{2}}}$

The parameter ${\\displaystyle \\mu }$ is the mean or expectation of the distribution (and also its median and mode), while the parameter ${\\displaystyle \\sigma }$ is its standard deviation. The variance of the distribution is ${\\displaystyle \\sigma ^{2}}$ . A random variable with a Gaussian distribution is said to be normally distributed, and is called a normal deviate.

(Wikipedia, The Free Encyclopedia, https://en.wikipedia.org/wiki/Normal_distribution)

Gaussian integral

Gaussian distribution

loi normale

French
loi de Gauss
loi de Laplace-Gauss
loi gaussienne

URI

http://data.loterre.fr/ark:/67375/PSR-XQF2FLQF-B

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