def mse(y_test, y_forecast):  # Completed
    """
    Computes the MSE error of two time series.
    """
    # Makes sure inputs are of the same length.
    try:
        assert len(y_test) == len(y_forecast)
    except AssertionError:
        raise NotImplementedError(
            "Tried to call MSE function with unbalanced data.")
    total = 0
    n = len(y_test)
    # Computes MSE using equation from lecture slide.
    for i in range(n):
        total += pow((y_test[i] - y_forecast[i]), 2)
    result = total/(n)
    print(f"Mean Square Error: {result:.2f}")
    return y_test