stat_sig_random_15

stat_sig_random_15.py

@njit(parallel=True)
def sample_diffs_in_rates(all_users, num_control_users, num_simulations):
    results = np.zeros(num_simulations)
    for i in prange(num_simulations):
        # numpy random shuffling appears to be slower when using numba
        random.shuffle(all_users)
        control_rate = all_users[:num_control_users].mean()
        # we assume the rest of the users are variant users
        variant_rate = all_users[num_control_users:].mean()
        results[i] = variant_rate - control_rate
    return results