def conf_inter(x, cl, s, n):
var_1 = n - 1
var_2 = subtract(1, cl)
var_3 = divide(var_2, 2)
var_4 = get_t_score(float(var_1), float(var_3))
var_5 = get_square_root(n)
var_6 = divide(s, var_5)
var_7 = multiply(float(var_4), var_6)
low = subtract(x, var_7)
high = add(x, var_7)
return [low, high]
def s_variance(data):
if is_valid(data):
size = len(data)
n = subtract(size, 1)
x = mean(data)
tmp = []
for i in data:
diff = subtract(i, x)
tmp.append(square(diff))
total = add_list(tmp)
return divide(total, n)
else:
raise TypeError("Data contains non-numeric values")
def sample_size_ci(z, p, w):
var_1 = divide(z, 2)
z_score = get_z_score(var_1)
e = divide(w, 2)
q = subtract(1, p)
var_2 = multiply(p, q)
var_3 = divide(float(z_score), e)
var_5 = square(var_3)
return multiply(var_2, var_5)
def median(num):
try:
num_values = len(num)
list_num = [num[i] for i in range(num_values)]
list_num.sort()
if num_values % 2 == 0:
median1 = list_num[int(num_values // 2)]
median2 = list_num[int(subtract((num_values // 2), 1))]
median_result = division(addition(median1, median2), 2)
else:
median_result = list_num[int(division(num_values, 2))]
return median_result
except ZeroDivisionError:
print("Error: Can't Divide by 0")
except ValueError:
print("Error: Check your data inputs")
def subtract(self, a, b):
self.result = subtract(a, b)
return self.result
def z_score(x, u, s):
var_1 = subtract(x, u)
return divide(var_1, s)