Bayes' Theorem for Everyone 01 - Introduction

Bayes' theorem is astonishing. You should not live your entire life without understanding Bayes' theorem. The understanding of Bayes' theorem has turned into a revolution among knowledgeable people, sometimes called Bayesians. And I have made this easy for everyone to understand.

Bayes' theorem starts with a simple statistical relationship, re-discovered many times throughout human history. But, the new Bayesian revolution isn't about the math. In the last few years mankind has gained an understanding of what Bayes' theorem means. And it's stunning.

Bayes shows the relationship between evidence in the world and our beliefs with mathematical precision. In other words, Bayes defines our relationship with reality. It's the backbone of clear thinking. It's used in science law and journalism, when everything's going the way it should. Bayes draws the line between rational and irrational. For many reasons, we can never know anything for sure. Once we accept that, Bayes is our best route to knowledge.

[thenosa]

I've never seen a person so passionate about a math topic. Good job

[RatherBAnon]

Great video. Taught me something I would not understand otherwise.

Your eyes pierce my soul though.

[peterlambrou]

I was looking to understand Bayes' theorem or Bayesian inferences just so I could understand an article I was reading.   I only need to go to the 'Peas' to understand as much as I needed. Mr. Napoletano may have gotten more detailed and in depth as he went on, but thankfully I only needed the first 2 segments.  This is truly the best tutorial on the subject for the average, non-math person.   Great job!

[sylvianguyen]

Nice intro, I stumbled upon this video by clicking on a few Big Think videos and I think this might be one of the most important rabbit hole I've ever dug myself. Looking forward to learning more about Bayes Theorem :)

[avieelicious]

He somehow reminded me of Sheldon Cooper, just saying

[josegomez]

He's like a real life Sheldon Cooper xD

[walawala]

Very nice. Your professor is in the zone. There is no method for judging whether human behaviour is rational that has so few problems as Bayes'.

[laurenb]

it's used as part of our cognitive psychology class as a standard for judging whether human behaviour is rational, particularly how people combine information to arrive at certain judgements.

[poloandscotch]

Does this bloke host 'Fun with Flags' too?

[timthompson]

I love learning math theorems from older Sheldon Cooper. :)

[RazaFayyaz]

You are the BEST!!! thank you for taking time for making this. I wish i had a teacher like you.

[LaureanoLuna]

Thanks, Nat.
These videos on conditional probability are unusually clear and honest.
I like your manners.

[andregeldenhuys]

Wow, first time I see one of your video's and I love love the way you explain it.

[walawala]

I was hoping that a significant point would come across. For 300 years Bayes theorem was a math topic. In the 1980s, we began to see that it’s at the root of all knowledge. This is a revolution.

[crazygamer]

Its for my psychology degree, part of the cognitive psychology lectures. Our lecturer spent about 4 lectures talking about the biases and the theory behind Bayes theorem.

[BiraDaniele]

Sir, I commend for your talent. Thank you for making this video series and excuse less intelligent people for being less intelligent.

[paulcunningham]

A lot of cognitive/behavioral psychologists are using Bayesian Statistics to understand how organisms process/use information to behave in ways appropriate to their environment. Charles Gallistel and Peter Balasm are among those psychologists (so if you're interested, I would recommend reading some of their stuff)

[veritybayes]

People ask me about this all the time because of my name, but I've never understood it. This was very informative!

[YouPokerAcademy]

This theorem plays a crucial role in the development of advanced poker understanding, and you've done a good job explaining it, so I'm adding you to my poker coaching channel right now!

[walawala]

Thanks Paul, I looked into Charles Gallistel. He summarizes the problem of priors beautifully, "The null is a precise hypothesis, while the alternatives to it are usually vague. Bayesian analysis penalizes vagueness: the vaguer the alternative, the more the null is favored when the observed effect is small."