PDF

PDF[dist,x]
gives the probability density function for the symbolic distribution dist evaluated at x.

PDF[dist,{x1,x2,}]
gives the multivariate probability density function for a symbolic distribution dist evaluated at .

PDF[dist]
gives the PDF as a pure function.

DetailsDetails

  • For discrete distributions, PDF is also known as a probability mass function.
  • For continuous distributions, PDF[dist,x] dx gives the probability that an observed value will lie between x and for infinitesimal dx.
  • For discrete distributions, PDF[dist,x] gives the probability that an observed value will be x.
  • For continuous multivariate distributions, PDF[dist,{x1,x2,}]dx1 dx2 gives the probability that an observed value will lie in the box given by the limits and for infinitesimal .
  • For discrete multivariate distributions, PDF[dist,{x1,x2,}] gives the probability that an observed value will be .

ExamplesExamplesopen allclose all

Basic Examples  (4)Basic Examples  (4)

The PDF of a univariate continuous distribution:

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The PDF of a univariate discrete distribution:

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The PDF of a multivariate continuous distribution:

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The PDF for a multivariate discrete distribution:

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Introduced in 2007
(6.0)
| Updated in 2010
(8.0)