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probability theory > probability density function

Terme préférentiel

probability density function  

Définition(s)

  • In probability theory, a probability density function (PDF), density function, or density of an absolutely continuous random variable, is a function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the random variable would be equal to that sample. Probability density is the probability per unit length, in other words, while the absolute likelihood for a continuous random variable to take on any particular value is 0 (since there is an infinite set of possible values to begin with), the value of the PDF at two different samples can be used to infer, in any particular draw of the random variable, how much more likely it is that the random variable would be close to one sample compared to the other sample.
    (Wikipedia, The Free Encyclopedia, https://en.wikipedia.org/wiki/Probability_density_function)

Concept(s) générique(s)

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URI

http://data.loterre.fr/ark:/67375/PSR-C4R6P0T9-G

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RDF/XML TURTLE JSON-LD Dernière modif. 12/10/2023