02 Experimental versus theoretical probability simulation#

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import random
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
import matplotlib.pyplot as plt
import seaborn as sns

khanacademy

Experimental versus theoretical probability simulation fig 1

def coin_trial():
    heads = 0
    for i in range(100):
        if random.random() <= 0.5:
            heads +=1
    return heads

coin_trial()

58

def simulate(n):
    trials = []
    for i in range(n):
        trials.append(coin_trial())
    return(sum(trials)/n)

simulate(1000)

50.136

# make similar simulation using numpy and shit get inspiration from DATACAMP

https://www.dataquest.io/blog/basic-statistics-in-python-probability/