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The Bayesian Trap

Veritasium2 HN recommenders · recommended in 2 months, 2017-2024
YouTube
4.5M views · 9 years ago · explainer · evergreen

Veritasium explains Bayes' theorem with examples and introduces the 'Bayesian trap', where repeated events get mistaken for inevitable ones. It discusses how priors shape our expectations and behavior.

HN points to it as an accessible introduction to Bayesian reasoning and as inspiration for personal projects.

Probability & game theoryData science & statistics#bayestheorem#priors#statistics#probability#reasoning

4 comments from Hacker News

@LolBatmanHuntsU2024 · in “Ask HN: What Are You Working On? (August 2024)”

Inspired by this Veritasium video: ▶ this video I'm working on a journal that incorporates Bayesian learning on how aspects of my life affect my mental, physical and social well-being. Having used it for nearly 500 days I plan to turn it into a life accounting and auditing tool. link

CitesView on HN
@tmamic2020 · in “Ask HN: How to choose which dentist or doctor to believe?”

So, in order to do your job of maintaining your health , you need need to do all of these jobs: 1. Learn about the symptoms, diagnosis, and treatment of your health problem 2. Assess the severity of the health problem 3. Learn about the experience of other people 4. Get multiple opinions Bonus: 5. Learn about multiple valid solutions 6. Find doctor's blind spots While doing all that, you pay for healthcare, which includes all that. You pay a doctor to know no1, do the no2, remember no3. You then pay for multiple of them to do the same. But then you still get to the point where you have to decide who to believe. And it would be easy if 4 of them say the same thing. You can be pretty sure they are right[1] because statistics. But what happens when they give multiple differing opinions, like here [2]. [1] ▶ this video [2] link

CitesView on HN
@partycoder2017 · in “Think Bayes: Bayesian Statistics Made Simple (2012)”

Another problem for the less familiar with the Bayes theorem is what is described as the "Bayesian trap", explained by the youtuber Veritasium: ▶ this video

RecommendsView on HN
@burntrelish12732017 · in “Receding glacier causes Canadian river to vanish in four days”

Definitely. Another good idea is to show the difference between reality and data can be overwhelmingly significant. Videos demonstrating this with examples: - "The Bayesian Trap" ▶ this video - "Is Most Research Wrong?" link

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