(name, mean, std)
return rv(name, NormalDistribution, (mean, std))
r"""
    Create a continuous random variable with a Normal distribution.

    The density of the Normal distribution is given by

    .. math::
        f(x) := \frac{1}{\sigma\sqrt{2\pi}} e^{ -\frac{(x-\mu)^2}{2\sigma^2} }

    Parameters
    ==========

    mu : Real number, the mean
    sigma : Real number, :math:`\sigma^2 > 0` the variance

    Returns
    =======

    A RandomSymbol.

    Examples
    ========

    >>> from sympy.stats import Normal, density, E, std, cdf, skewness
    >>> from sympy import Symbol, simplify, pprint, factor, together, factor_terms

    >>> mu = Symbol("mu")
    >>> sigma = Symbol("sigma", positive=True)
    >>> z = Symbol("z")

    >>> X = Normal("x", mu, sigma)

    >>> density(X)(z)
    sqrt(2)*exp(-(-mu + z)**2/(2*sigma**2))/(2*sqrt(pi)*sigma)

    >>> C = simplify(cdf(X))(z) # it needs a little more help...
    >>> pprint(C, use_unicode=False)
       /  ___          \
       |\/ 2 *(-mu + z)|
    erf|---------------|
       \    2*sigma    /   1
    -------------------- + -
             2             2

    >>> simplify(skewness(X))
    0

    >>> X = Normal("x", 0, 1) # Mean 0, standard deviation 1
    >>> density(X)(z)
    sqrt(2)*exp(-z**2/2)/(2*sqrt(pi))

    >>> E(2*X + 1)
    1

    >>> simplify(std(2*X + 1))
    2

    References
    ==========

    .. [1] http://en.wikipedia.org/wiki/Normal_distribution
    .. [2] http://mathworld.wolfram.com/NormalDistributionFunction.html
r"""
    Create a continuous random variable with a Normal distribution.
r Create a continuous random variable with a Normal distribution .
def Normal(name, mean, std):
    r"""
    Create a continuous random variable with a Normal distribution.

    The density of the Normal distribution is given by

    .. math::
        f(x) := \frac{1}{\sigma\sqrt{2\pi}} e^{ -\frac{(x-\mu)^2}{2\sigma^2} }

    Parameters
    ==========

    mu : Real number, the mean
    sigma : Real number, :math:`\sigma^2 > 0` the variance

    Returns
    =======

    A RandomSymbol.

    Examples
    ========

    >>> from sympy.stats import Normal, density, E, std, cdf, skewness
    >>> from sympy import Symbol, simplify, pprint, factor, together, factor_terms

    >>> mu = Symbol("mu")
    >>> sigma = Symbol("sigma", positive=True)
    >>> z = Symbol("z")

    >>> X = Normal("x", mu, sigma)

    >>> density(X)(z)
    sqrt(2)*exp(-(-mu + z)**2/(2*sigma**2))/(2*sqrt(pi)*sigma)

    >>> C = simplify(cdf(X))(z) # it needs a little more help...
    >>> pprint(C, use_unicode=False)
       /  ___          \
       |\/ 2 *(-mu + z)|
    erf|---------------|
       \    2*sigma    /   1
    -------------------- + -
             2             2

    >>> simplify(skewness(X))
    0

    >>> X = Normal("x", 0, 1) # Mean 0, standard deviation 1
    >>> density(X)(z)
    sqrt(2)*exp(-z**2/2)/(2*sqrt(pi))

    >>> E(2*X + 1)
    1

    >>> simplify(std(2*X + 1))
    2

    References
    ==========

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

    return rv(name, NormalDistribution, (mean, std))
def Normal ( name , mean , std ) : return rv ( name , NormalDistribution , ( mean , std ) )