def sum_of_squares(obs, pred):
return np.sum((np.array(obs) - np.array(pred)) ** <NUM_LIT:2>)<EOL>
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.