code: def outlier_cutoff(a, threshold=3.5):
      
      A = np.array(a, dtype=float)
      M = np.median(A)
      D = np.absolute(A - M)
      MAD = np.median(D)
      C = threshold / .67449 * MAD
      return M - C, M + C
docs: Iglewicz and Hoaglin's robust, returns the cutoff values - lower bound and
      upper bound.