Compute the PDF of a Continuous Random Variable - Maple Programming Help

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Compute the PDF of a Continuous Random Variable

 Description Compute the PDF (probability density function) of a continuous random variable.

Define a random variable using the built-in probability distributions or by creating a custom distribution. The parameters of the distributions can be symbolic, numeric, or a mix.

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Evaluate the PDF of the random variable at a point. The point can be numeric or symbolic.

 > $s:=\mathrm{Statistics}\left[\mathrm{PDF}\right]\left(X,{t}\right)$
 $\colorbox[rgb]{0,0,0}{{s}}\colorbox[rgb]{0,0,0}{{:=}}\colorbox[rgb]{0,0,0}{{{}}\begin{array}{cc}\colorbox[rgb]{0,0,0}{{0}}& \colorbox[rgb]{0,0,0}{{t}}\colorbox[rgb]{0,0,0}{{<}}\colorbox[rgb]{0,0,0}{{0}}\\ \frac{{\left(\frac{\colorbox[rgb]{0,0,0}{{t}}}{\colorbox[rgb]{0,0,0}{{a}}}\right)}^{\colorbox[rgb]{0,0,0}{{b}}\colorbox[rgb]{0,0,0}{{-}}\colorbox[rgb]{0,0,0}{{1}}}\colorbox[rgb]{0,0,0}{{}}{\colorbox[rgb]{0,0,0}{{ⅇ}}}^{\colorbox[rgb]{0,0,0}{{-}}\frac{\colorbox[rgb]{0,0,0}{{t}}}{\colorbox[rgb]{0,0,0}{{a}}}}}{\colorbox[rgb]{0,0,0}{{a}}\colorbox[rgb]{0,0,0}{{}}\colorbox[rgb]{0,0,0}{{\mathrm{Γ}}}\colorbox[rgb]{0,0,0}{{}}\left(\colorbox[rgb]{0,0,0}{{b}}\right)}& \colorbox[rgb]{0,0,0}{{\mathrm{otherwise}}}\end{array}$ (1)
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