code: def sum_of_squares(obs, pred):
      
  
      return np.sum((np.array(obs) - np.array(pred)) ** 2)
docs: Sum of squares between observed and predicted data
  
      Parameters
      ----------
      obs : iterable
          Observed data
      pred : iterable
          Predicted data
  
      Returns
      -------
      float
          Sum of squares
  
      Notes
      -----
      The length of observed and predicted data must match.