code: def norm_cdf(x_range, mu, var=1, std=None):
      
  
      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))
docs: 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%.