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The Most Important Concept in Probability: Bayes' Theorem (Part 1)
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Today's video is the first of a multi-part series on Bayesian methods! We'll derive Bayes' theorem, demonstrate how it allows us to update our beliefs with new information, and we'll apply it to a realistic problem.
0:00 Bayesian Methods Introduction
0:42 Deriving Bayes' Theorem - Events and Probabilities
2:04 Conditional Probabilities and Bayes' Theorem
4:18 Updating Beliefs via Bayes' Theorem - Shipping a Product
7:30 Application of Bayes' Theorem - Medical Test Problem
10:11 The Two Key Factors that Influence Updated Beliefs
11:28 Key Bayesian Terminology
12:17 Bayesian Statistics Motivation
#probability #mathematics #datascience #tutorial #bayestheorem
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If this is your first video, welcome! I am a professor sharing educational resources around probability, statistics, optimization methods, algorithms, and programming to a broad audience.
Outside of YouTube, you can currently find me in Vancouver, Canada at the University of British Columbia.
Thank you, and I look forward to seeing you in future videos!
0:00 Bayesian Methods Introduction
0:42 Deriving Bayes' Theorem - Events and Probabilities
2:04 Conditional Probabilities and Bayes' Theorem
4:18 Updating Beliefs via Bayes' Theorem - Shipping a Product
7:30 Application of Bayes' Theorem - Medical Test Problem
10:11 The Two Key Factors that Influence Updated Beliefs
11:28 Key Bayesian Terminology
12:17 Bayesian Statistics Motivation
#probability #mathematics #datascience #tutorial #bayestheorem
=====================
======================
If this is your first video, welcome! I am a professor sharing educational resources around probability, statistics, optimization methods, algorithms, and programming to a broad audience.
Outside of YouTube, you can currently find me in Vancouver, Canada at the University of British Columbia.
Thank you, and I look forward to seeing you in future videos!
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