def created_sample_correlation(datax, datay):
meanx = created_mean(datax)
meany = created_mean(datay)
sumprod = 0.0
sumx = 0.0
sumy = 0.0
for k in range(len(datax)):
temp = multiply(subtract(datax[k], meanx), subtract(datay[k], meany))
sumprod = add(sumprod, temp)
sumx = add(sumx, square(subtract(datax[k], meanx)))
sumy = add(sumy, square(subtract(datay[k], meany)))
corr = division(sumprod, multiply(square_root(sumx), square_root(sumy)))
return "{0:.2f}".format(round(corr, 2))
def created_mean(data):
total = 0.0
for k in range(len(data)):
total = add(total, data[k])
result = division(total, len(data))
return "{0:.2f}".format(round(result, 2))
def created_variance2(data):
meanx = created_mean(data)
sumx = 0.0
for k in range(len(data)):
temp = square(subtract(data[k], meanx))
sumx = add(sumx, temp)
return "{0:.2f}".format(round(sumx / (len(data)), 2))
def created_mean_deviation(datax):
meanx = created_mean(datax)
sumx = 0.0
for k in range(len(datax)):
diff = abs(subtract(datax[k], meanx))
sumx = add(sumx, diff)
mean_dev = division(sumx, len(datax))
return "{0:.2f}".format(round(mean_dev, 2))
def test_add(self):
self.assertEqual(add(10,20), 30.0)