(name, alpha, beta)
return rv(name, BetaDistribution, (alpha, beta))
r"""
    Create a Continuous Random Variable with a Beta distribution.

    The density of the Beta distribution is given by

    .. math::
        f(x) := \frac{x^{\alpha-1}(1-x)^{\beta-1}} {\mathrm{B}(\alpha,\beta)}

    with :math:`x \in [0,1]`.

    Parameters
    ==========

    alpha : Real number, `\alpha > 0`, a shape
    beta : Real number, `\beta > 0`, a shape

    Returns
    =======

    A RandomSymbol.

    Examples
    ========

    >>> from sympy.stats import Beta, density, E, variance
    >>> from sympy import Symbol, simplify, pprint, expand_func

    >>> alpha = Symbol("alpha", positive=True)
    >>> beta = Symbol("beta", positive=True)
    >>> z = Symbol("z")

    >>> X = Beta("x", alpha, beta)

    >>> D = density(X)(z)
    >>> pprint(D, use_unicode=False)
     alpha - 1         beta - 1
    z         *(-z + 1)
    ---------------------------
         beta(alpha, beta)

    >>> expand_func(simplify(E(X, meijerg=True)))
    alpha/(alpha + beta)

    >>> simplify(variance(X, meijerg=True))  #doctest: +SKIP
    alpha*beta/((alpha + beta)**2*(alpha + beta + 1))

    References
    ==========

    .. [1] http://en.wikipedia.org/wiki/Beta_distribution
    .. [2] http://mathworld.wolfram.com/BetaDistribution.html
r"""
    Create a Continuous Random Variable with a Beta distribution.
r Create a Continuous Random Variable with a Beta distribution .
def Beta(name, alpha, beta):
    r"""
    Create a Continuous Random Variable with a Beta distribution.

    The density of the Beta distribution is given by

    .. math::
        f(x) := \frac{x^{\alpha-1}(1-x)^{\beta-1}} {\mathrm{B}(\alpha,\beta)}

    with :math:`x \in [0,1]`.

    Parameters
    ==========

    alpha : Real number, `\alpha > 0`, a shape
    beta : Real number, `\beta > 0`, a shape

    Returns
    =======

    A RandomSymbol.

    Examples
    ========

    >>> from sympy.stats import Beta, density, E, variance
    >>> from sympy import Symbol, simplify, pprint, expand_func

    >>> alpha = Symbol("alpha", positive=True)
    >>> beta = Symbol("beta", positive=True)
    >>> z = Symbol("z")

    >>> X = Beta("x", alpha, beta)

    >>> D = density(X)(z)
    >>> pprint(D, use_unicode=False)
     alpha - 1         beta - 1
    z         *(-z + 1)
    ---------------------------
         beta(alpha, beta)

    >>> expand_func(simplify(E(X, meijerg=True)))
    alpha/(alpha + beta)

    >>> simplify(variance(X, meijerg=True))  #doctest: +SKIP
    alpha*beta/((alpha + beta)**2*(alpha + beta + 1))

    References
    ==========

    .. [1] http://en.wikipedia.org/wiki/Beta_distribution
    .. [2] http://mathworld.wolfram.com/BetaDistribution.html
    """

    return rv(name, BetaDistribution, (alpha, beta))
def Beta ( name , alpha , beta ) : return rv ( name , BetaDistribution , ( alpha , beta ) )