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import numpy as np

def compute_r_squared(data, predictions):
    # Write a function that, given two input numpy arrays, 'data', and 'predictions,'
    # returns the coefficient of determination, R^2, for the model that produced 
    # predictions.
    # 
    # Numpy has a couple of functions -- np.mean() and np.sum() --
    # that you might find useful, but you don't have to use them.

    # YOUR CODE GOES HERE
    # Calculate denominator
    SST = ((data - np.mean(data)) **2).sum()
    # Calculate numerator
    SSReg = ((predictions-data)**2).sum()
    r_squared = 1 - SSReg / SST

    return r_squared