Game Theory 101 (#71): Bayes' Rule

This lecture introduces Bayes' rule, the way to update one's beliefs in light of new information. We primarily use Bayes' rule in sequential move games of incomplete information, but it pops up a little bit in simultaneous move games as well. It also provides a hint for why we have been using BAYESIAN Nash equilibrium in this unit.

[jiabihe]

Your graph really helps me understand the Bayes' rule! Thank you so much!

[PunmasterSTP]

I’ll skip making a joke given the serious nature of the example, but I’ll thank you again for such a great video series. And I’d also like to say to anyone scrolling through the comments, that knowing this information and how to use the logic can help you and your loved ones make more informed decisions in case you (or they) find yourself in this truly unfortunate situation.

[IvoPetrov]

Great video! I'd just want to point something out, there is a different way of thinking about this that I personally find easier: P(A!B) = P(A und B)/P(B) ; the probability of A occurring, given the occurrence of B is the probability that both occur divided by the sum of probabilities of B occurring. Have a great day!

[Anuttymous]

Are any of these most recent lectures (and ideally coming ones) available in print/text? I got your Game Theory 101 book from Amazon, but you've obviously started more lectures that don't appear to be covered in it.

[wenshan]

may i ask where is the next lecture continuing from this?

[ayylmao]

how on EARTh did you arrive at the conclusion 3/23 = 13%

[mithilarids]

Your video was really helpful in understanding the bayes rule. But you could definitely used better example.. An example of "you having cancer" sucks..

[gregslu]

You could pick happier example, hearing "you have x% chances of having cancer" for 13 min is not fun

[Diana.Stavel]

Your videos are cool! But, please, choose more ''ecological'' examples. Or, at least, saying that John has a cancer...