
{{alias}}( [n, p] )
    Returns a binomial distribution object.

    Parameters
    ----------
    n: integer (optional)
        Number of trials. Must be a positive integer. Default: `1`.

    p: number (optional)
        Success probability. Must be a number between `0` and `1`. Default:
        `0.5`.

    Returns
    -------
    binomial: Object
        Distribution instance.

    binomial.n: number
        Number of trials. If set, the value must be a positive integer.

    binomial.p: number
        Success probability. If set, the value must be a number between `0` and
        `1`.

    binomial.kurtosis: number
        Read-only property which returns the excess kurtosis.

    binomial.mean: number
        Read-only property which returns the expected value.

    binomial.median: number
        Read-only property which returns the median.

    binomial.mode: number
        Read-only property which returns the mode.

    binomial.skewness: number
        Read-only property which returns the skewness.

    binomial.stdev: number
        Read-only property which returns the standard deviation.

    binomial.variance: number
        Read-only property which returns the variance.

    binomial.cdf: Function
        Evaluates the cumulative distribution function (CDF).

    binomial.logpmf: Function
        Evaluates the natural logarithm of the probability mass function (PMF).

    binomial.mgf: Function
        Evaluates the moment-generating function (MGF).

    binomial.pmf: Function
        Evaluates the probability mass function (PMF).

    binomial.quantile: Function
        Evaluates the quantile function at probability `p`.

    Examples
    --------
    > var binomial = {{alias}}( 8, 0.5 );
    > binomial.n
    8.0
    > binomial.p
    0.5
    > binomial.kurtosis
    -0.25
    > binomial.mean
    4.0
    > binomial.median
    4.0
    > binomial.mode
    4.0
    > binomial.skewness
    0.0
    > binomial.stdev
    ~1.414
    > binomial.variance
    2.0
    > binomial.cdf( 2.9 )
    ~0.145
    > binomial.logpmf( 3.0 )
    ~-1.52
    > binomial.mgf( 0.2 )
    ~2.316
    > binomial.pmf( 3.0 )
    ~0.219
    > binomial.quantile( 0.8 )
    5.0

    See Also
    --------

