(symbol, density, set=Interval(-oo, oo))
return SingleContinuousPSpace(symbol, dist).value
Create a Continuous Random Variable given the following:

    -- a symbol
    -- a probability density function
    -- set on which the pdf is valid (defaults to entire real line)

    Returns a RandomSymbol.

    Many common continuous random variable types are already implemented.
    This function should be necessary only very rarely.

    Examples
    ========

    >>> from sympy import Symbol, sqrt, exp, pi
    >>> from sympy.stats import ContinuousRV, P, E

    >>> x = Symbol("x")

    >>> pdf = sqrt(2)*exp(-x**2/2)/(2*sqrt(pi)) # Normal distribution
    >>> X = ContinuousRV(x, pdf)

    >>> E(X)
    0
    >>> P(X>0)
    1/2
Create a Continuous Random Variable given the following:
Create a Continuous Random Variable given the following :
def ContinuousRV(symbol, density, set=Interval(-oo, oo)):
    """
    Create a Continuous Random Variable given the following:

    -- a symbol
    -- a probability density function
    -- set on which the pdf is valid (defaults to entire real line)

    Returns a RandomSymbol.

    Many common continuous random variable types are already implemented.
    This function should be necessary only very rarely.

    Examples
    ========

    >>> from sympy import Symbol, sqrt, exp, pi
    >>> from sympy.stats import ContinuousRV, P, E

    >>> x = Symbol("x")

    >>> pdf = sqrt(2)*exp(-x**2/2)/(2*sqrt(pi)) # Normal distribution
    >>> X = ContinuousRV(x, pdf)

    >>> E(X)
    0
    >>> P(X>0)
    1/2
    """
    pdf = Lambda(symbol, density)
    dist = ContinuousDistributionHandmade(pdf, set)
    return SingleContinuousPSpace(symbol, dist).value
def ContinuousRV ( symbol , density , set = Interval ( - oo , oo ) ) : pdf = Lambda ( symbol , density ) dist = ContinuousDistributionHandmade ( pdf , set ) return SingleContinuousPSpace ( symbol , dist ) . value