def MarginError(data):
List = []
SE = (StdDevSample(data) / (squareRoot(len(data))))
for i in Z_scores(z_values(data)):
ME = i * SE
List.append(ME)
return List
def Sample_Correlation(list1, list2):
n = len(list1)
avg_x = average(list1)
avg_y = average(list2)
rod = 0
x2 = 0
y2 = 0
for i in range(n):
x = subtraction(list1[i], avg_x)
y = subtraction(list2[i], avg_y)
rod += product(x, y)
x2 += square(x)
y2 += square(y)
return rod / squareRoot(x2 * y2)
def SquareRoot(self, a):
if typeFunction(a) == True:
self.result = squareRoot(a)
return self.result
def test_squareRoot(self):
self.assertEqual(5, squareRoot(25))
def population_variance(data):
x = StdDevPop(data)
return squareRoot(x)
def sample_variance(data):
x = StdDevSample(data)
return squareRoot(x)