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  2. Artificial Intelligence
  3. Statistics and Machine Learning
  4. Basic Statistics Warmup
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Basic Statistics Warmup

  • ericstricker73
     + 1 comment
    import pandas as pd
import numpy as np
import math

def custom_round(num, decimals=0):
    factor = 10 ** decimals
    return math.floor(num * factor + 0.5) / factor

i = input()
s = input()
l = list(map(int, s.split(" ")))
numbers_series = pd.Series(l)

#Calculate the mean
mean = numbers_series.mean()
print(f"{custom_round(mean,1):.1f}")

#Median
print(f"{custom_round(numbers_series.median(),1):.1f}")

#mode (which is a lsit)
mode = numbers_series.mode()
print(f"{mode[0]}")

std = numbers_series.std(ddof=0)
print(f"{custom_round(std,1):.1f}")


#Find the critical value for a 95% confidence interval
margin_of_error = 1.96 * (std / (len(numbers_series) ** 0.5))
#margin_of_error = confidence_level * (std/(np.sqrt(len(numbers_series))))

#Calculate the confidence interval
lower_bound = mean - margin_of_error
upper_bound = mean + margin_of_error

print(f"{custom_round(lower_bound,1):.1f} {custom_round(upper_bound,1):.1f}")