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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def norm_cdf(x_range, mu, var=1, std=None):
 """ Computes the probability that a Gaussian distribution lies within a range of values. Parameters x_range : (float, float) tuple of range to compute probability for mu : float mean of the Gaussian var : float, optional variance of the Gaussian. Ignored if `std` is provided std : float, optional standard deviation of the Gaussian. This overrides the `var` parameter Returns ------- probability : float probability that Gaussian is within x_range. E.g. .1 means 10%. """


    if std is None:
        std = math.sqrt(var)
    return abs(norm.cdf(x_range[0], loc=mu, scale=std) -
               norm.cdf(x_range[1], loc=mu, scale=std))