bayesian-inference

Welcome to #bayesian-inference!

This is the start of the Bayesian Inference module notes.

Aryan S. BOT Today at 10:42 AM

Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available.

Equation
P(A|B) = [P(B|A) ยท P(A)] / P(B)
Aryan S. BOT Today at 10:45 AM

Here is the Python simulation code for the coin flip experiment:

python Copy 
import numpy as np

# 1. Define Prior
prior = np.ones(100) / 100 
p_grid = np.linspace(0, 1, 100)

def update(prior, heads, total):
    likelihood = p_grid**heads * (1 - p_grid)**(total - heads)
    posterior = likelihood * prior
    return posterior / posterior.sum()