YoVDO

Probability via Computation - Week 4

Offered By: The Julia Programming Language via YouTube

Tags

Probability Courses Data Visualization Courses Central Limit Theorem Courses Monte Carlo Simulation Courses Uniform Distribution Courses Computational Statistics Courses

Course Description

Overview

Explore probability concepts through computational methods in this 26-minute video lecture from MIT's 18.S191 Fall 2020 course. Learn how to model epidemic propagation, perform random sampling using rand(), and conduct classic experiments like rolling dice. Dive into Monte Carlo simulations to plot frequencies and understand relative frequency. Examine random variables, uniform random numbers, and visualize pre-generated data. Investigate Bernoulli trials, including the algorithm and probability distribution. Conclude with an illustration of the Central Limit Theorem by flipping many biased coins. Gain practical insights into probability theory through hands-on computational examples.

Syllabus

How to model epidemic propagation?.
Random Sampling using rand().
Classic experiment of Rolling a die.
Monte Carlo Simulation to plot the frequencies.
Relative frequency or proportion of rolls of the die.
Random variables.
Uniform random numbers.
Visualization: plotting the pre-generated data.
Sample events with a given probability: Bernoulli trials.
Algorithm.
What is Bernoulli random variable?.
Probability distribution of random variable.
Flipping many biased coins.
Illustration of Central Limit Theorem.


Taught by

The Julia Programming Language

Related Courses

Introduction to Computational Finance and Financial Econometrics
University of Washington via Coursera
Math behind Moneyball
University of Houston System via Coursera
La gestión de los riesgos y la administración de los cambios en el proyecto
University of California, Irvine via Coursera
Introduction to Spreadsheets and Models
University of Pennsylvania via Coursera
Managing Uncertainty in Marketing Analytics
Emory University via Coursera