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)