Python-Read data from a numeric data file and calculate covariance

A program that reads data from a tab-delimited numeric data series file and calculates covariance.

MultipleRegressionAnalysis_Data1.txt

65.7	67.8	70.3	72.0	74.3	76.2
3.27	3.06	4.22	4.10	5.26	6.18
69.7	69.7	71.3	77.6	81.0	78.7

correlation.py

import numpy as np

def load_data(filename):
    x = []
    for line in open(filename, 'r'):
        x.append([])
        for data in line.strip().split('\t'):
            x[len(x)-1].append(float(data))
    return x

def calc_correlation(data1, data2):
    ave1 = calc_average(data1)
    ave2 = calc_average(data2)
    sum = 0.0
    for i in range(len(data1)):
        sum += data1[i] * data2[i]
    return (sum / len(data1)) - (ave1 * ave2)
    
def calc_average(data):
    sum = 0.0
    for d in data:
        sum += d
    return sum / len(data)

if __name__ == "__main__":
    data = load_data('MultipleRegressionAnalysis_Data1.txt')
    corr = []
    for i in range(len(data)):
        corr.append([])
        for j in range(len(data)):
            corr[len(corr)-1].append(calc_correlation(data[i],data[j]))
            
    print(np.array(corr))

result

>python correlation.py
[[ 12.95583333   3.70208333  14.89666667]
 [  3.70208333   1.18114722   4.10327778]
 [ 14.89666667   4.10327778  20.94222222]]