def pvalue(lst):
lst = []
x = len(lst)
score = zscore(lst)
for i in y:
if i == score:
lst.append(y)
return y
def P_value(data):
data = []
n = len(data)
score = zscore()
for index in n:
if n == score:
data.append(index)
return index
def zscore(self, data, x):
self.result = zscore(data, x)
return self.result
def confidence_interval_SUB(confidence_interval_SUB_list):
return subtraction(
population_mean(confidence_interval_SUB_list),
(multiplication(zscore(confidence_interval_SUB_list)),
division(population_standard_deviance(confidence_interval_SUB_list),
square_root(num_values))))
def zscore(self):
self.result = zscore(self.zscore_list)
return self.result
def z_score(self, a):
self.result = zscore(a)
return self.result
def zscore(self, a):
self.result = zscore(a)
def zscore(self, a, b, c):
self.result = zscore(a, b, c)
return self.result