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# CRITICAL THINKING – Fundamentals: Bayes' Theorem [HD]

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35 thoughts on “CRITICAL THINKING – Fundamentals: Bayes' Theorem [HD]”

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thanks but i thought first Sally is a guy's name. so i was a lil confused at first.

Thank you!

Beautiful video! Really helped me conceptualize what is actually going on here. Although I think I may have hypothesitis now.

Excellent approach. Thank You!

this makes a lot of sense. thx

"key to understanding what it means to think rationally" .. Ironically this theorem is used for the most irrational purposes. Biggest example is in adjudication new medicines i.e. proving efficacy of new medicines in several disease therapies. Seems like Statisticians can prove / disprove anything with Bayes theorem.

i love the comments here…..very thought provoking

What if Sally was gender fluid?

You sexist bastard. Im triggered!

Cool vid by the way.

Have spent too much time searching for resources to break down and explain this theorem; this 6 minute video trumps all. Well done and thanks Ian.

Thank you for the excellent explanation!

That was great thanks!

조건부확률

it's so cool , great explaination =))

Bayes' Theorem points out the dependence of statistical reasoning on descriptions of events or states of affairs. If your starting point is that someone may have hypothesitis, it raises the questions not just of what is the probability of these symptoms in a hypothesitis patient (hp), but what is the probability of hypothesitis in a patient with these symptoms. But these just raise more questions about proper description of the relevant population. Not just what is the probability of hypothesitis in the people of where – this class, this town, this region, the earth? And not just all that but what is the probability of hypothesitis in a member of this population at this moment? The disease is presumably not a static thing, but a process over time. And then, what is the probability of someone in this population right now being a hp given other variables? In other words, the formula might give a reasonable way to draw conclusions assuming we have a good understanding of what level of ignorance we are at and how close we are to having that magical description at which the probability is either one or zero. It is tempting to think we have some basic question of the form, "What is the probability of X, simpliciter," but how often do we have such a question?

Did you just assumed sally's gender?

Short but not an insufficient to understand

Great lecture, simply wow teaching 👌👍

This is a perfect explanation!

Great Video!!! Have been struggling to understand this concept but you have made it simple and clear for me. Thank you so much!! 🙂

Great vid. Watch this vid after working through/with the multiplication rule of independence for at least a little bit.

I always enjoy seeing how the logic that I use pretty much without realizing why can be broken down and explained so that other people who don't possess the same quality of innate faculties can have it explained to them.

did you just assume sally's gender?

Excellent, Thanks

I can't stand that fake hand effect so i couldn't watch this video even though i wanted to

You explained it really well ..

If it's the case that someone has a flu and recovered later on, or that someone has passed on the flu, or even the number of students will change as the time pass, can we say that probability is inaccurate? Is probability relates to judgement under closed and static conditions with prior sufficient knowledge? But if this is the case, how can we apply probability in the changing, unpredictable real world?

thank you so much because NOW I am convinced that the the prior probability based on conditional probability to the hypothesis that I might be somewhat STUPID is basically a hypothesitis that is a 100 percent evidently true…you scmuck….

First video I finally understood!!

Great stuff . Couldn't have explained better (y)

DID YOU JUST ASSUME SALLY'S GENDER??!!

Nice man. God bless you

Great video, thanks!

I like quiet people, you are quiet, 100 percent of dead people are quiet therefore you must be dead

Nice job

super thala, kalakitenga, super good