08 Compound probability of independent events#

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

khanacademy

Compound probability of independent events fig 1Compound probability of independent events fig 2

coin = ['H', 'T']

def P(cond, total_lst):
    cond_lst = list(filter(cond, total_lst))
    return len(cond_lst) / len(total_lst), cond_lst

# P(H)
p_heads, _ = P(lambda x: x == 'H', coin)
print(p_heads)

0.5

# P(HH) = P(H) . P(H)
p_heads_heads = P(lambda x: x == 'H', coin)[0] * P(lambda x: x == 'H', coin)[0]
print(p_heads_heads)

0.25

# P(THT)
p_tails_heads_tails =P(lambda x: x == 'T', coin)[0] * P(lambda x: x == 'H', coin)[0] *  P(lambda x: x == 'T', coin)[0]
print(p_tails_heads_tails)

0.125