W3_L3: Simulation of expected value using python
Welcome to Week 3 Lecture 3 of the course "Statistics for Data Science - II" by Prof. Andrew Thangaraj.
Full Course: https://study.iitm.ac.in/ds/course_pa...
Video Overview
This lecture revisits the concept of expectations and shows how simulations in Python can be used to verify and strengthen understanding. We simulate casino dice games and the classic balls and bins experiment comparing the simulated results to theoretical expected values. This practical approach helps visualize and confirm the connection between expected value and long term averages.The lecture uses the scipy.stats module to generate random variables from common distributions such as binomial geometric and Poisson. While not a coding tutorial the lecture clearly explains the logic behind the simulations and their role in probability theory and data science.
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