def z_score_list(data):
if is_valid(data):
tmp = []
u = mean(data)
s = standard_deviation(data)
for x in data:
tmp.append(z_score(x, u, s))
return tmp
else:
raise TypeError("Data contains non-numeric values")
def variance(data):
if is_valid(data):
size = len(data)
x = mean(data)
tmp = []
for i in data:
diff = subtract(i, x)
tmp.append(square(diff))
total = add_list(tmp)
return divide(total, size)
else:
raise TypeError("Data contains non-numeric values")
def standard_deviation(data):
if is_valid(data):
var = variance(data)
return get_square_root(var)
else:
raise TypeError("Data contains non-numeric values")
def mode(self, data):
if is_valid(data):
self.result = mode(data)
return self.result
else:
raise TypeError("Data contains non-numeric values")