add base utils for predictor

predictor/model/utils.py

 import json
 import random
 
+def calc_stat(numbers):
+    mu = sum(numbers) / len(numbers)
+    sigma = (sum([(x - mu) ** 2 for x in numbers]) / len(numbers)) ** 0.5
+    return mu, sigma
+
+
+def conf_inv(mu, sigma, n):
+    delta = 2.776 * sigma / (n ** 0.5)  # 95%
+    return mu - delta, mu + delta
+
 
 def arg_min(lst):
     m = float('inf')