CRITICAL THINKING - Fundamentals: Bayes' Theorem [HD]

[@mobile012]

Best simple presentation of Bayes' Theorem I've seen so far. Thanks for the video.

[@ahmed1800XY]

The Best and most straightforward explanation that I have seen. There are so many videos out there...very confusing.

[@WirelessPhilosophy]

Glad it was helpful!

[@anticorncob6]

I prefer Baye’s theorem as P(A|B)*P(B)=P(B|A)*P(A) Easy to remember and symmetric. And it’s also helpful because sometimes it’s the conditional probability you’re solving for

[@trs_4612]

i can't start to imagine a venn diagrams with more than 5 circles. also think about conditional probability for that!!!

[@joejoe-lb6bw]

There are a lot of good Bayes videos out there with all the boxes and explanations. This one just cuts straight to the point and gives a very simple example that we can relate to. Excellent.

[@ostihpem]

Could u guys make two videos that explain Gödel's incompleteness theorems without too much details, but detailed enough to understand the idea?

[@austinlindsey3836]

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.

[@Thetarget1]

That was a really understandable example. Though terms like "P of H given E" and "P of E given H" mess up my head. WIll you be making a video on how this relates to the philosophy of science?

[@hemm2333]

After watching many videos on this concept and pulling my hair off, finally ended with this best explanation video. Thanks ❤

[@WirelessPhilosophy]

Glad it helped!

[@sukgihong4740]

I currently study entry-level data science, and this is reall helpful. Thanks a lot for the video. BTW, can you let me know what video editing tools did you use to make this?

[@bikefarmtaiwan1800]

You did a great job of introducing this theory. You have the right talents to do well with these kinds of videos.

[@daviddemar8749]

Omg! ian im an atty assistant to a nys supreme ct. Justice. I've never taken a probability/statistics class. My judge has a matter pending before him right now which amongst other science related topics, involves Bayesian probability. Well thanks to you and this amazing video [unlike others I've watched this week, fruitlessly ] I get it now, I get it now!!!!! You are now one of my heroes- a gold medalist MATHLETE. Thank you and good luck and much success in your studies and in all of your endeavors. 😊 now let's cure Hypothesitis!

[@oliverfarrant3718]

Fantastic vid, Ian is great at explaining the concept

[@BorisLikesBeer13]

Very nice video, i recently went to a presentation about the power of evidence in criminal law and they used Bayes' Theorem to calculate the power of the evidence. Liked and subbed

[@samanthaeves2967]

This was a fantastic video. I'm going to a CUNY school for undergrad and this video makes me proud of it :)

[@rishisingh6111]

The BEST presentation of the concept I have seen so far; thanks a ton!

[@ridhikakhanna6383]

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

[@galanoftaa6439]

I've a bunch a videos online trying to explain Bayes Rules. This one is the best I've seen so far. If you guys have a problem with this video you should see some of the other stuff out there.

[@simonzak1407]

Absolutely so cool. A tool looking specifically at the situation where we grant that we don’t know whether something is true.

[@cosmicwarriorx1]

11 years after taking the IIT Entrance exam... finally, today I understood what it is.. thanks... 😂😁😊

[@रिवायत]

Short but not an insufficient to understand Great lecture, simply wow teaching 👌👍

[@-8l-924]

this was excellent. I was reading a paper recently and it used P(E|H) with those letters representing Evidence and Hypothesis, just like this video uses, but I couldn't understand how to interpret that proposition. this was very helpful for that piece I happened to run into, let alone explaining the theorem itself.

[@joestudent7160]

thumbs up! short and effective intro to Bayes Theorem

[@WirelessPhilosophy]

Glad you liked it!

[@alwaysovercomingbear4809]

This would be useful for society to remember this, right now!

[@teckyify]

Did you actually explained how the formula is derived? I can't see that, just plain "put you values inside this black box".

[@MichaelGTadesse]

Thanks a really informative and explanatory video for beginners in Bayes' Theorem! Keep up the good job

[@kashifsmith4037]

Great explanation, this video has been the most helpful to me all the vids on this topic I've seen and the video length is perfect too.

[@henryt.9821]

Your handwriting is godly.

[@SoSoKayla]

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.

[@arj123sub]

I believe I finally understand Bayes after this video!! Thanks

[@spankymebottom]

ty. first video on the topic that didn't give me a headache

[@ivancarlson953]

If the P(H given E) = 0.00095, does that mean that (1-0.00095)=0.99905 is the P(not H given E) and thus, it's very unlikely that one has H given E, and very likely that one does not have H given E?

[@sandyj342]

Best explanation I have seen so far!

[@jwalk121]

critical thinking should be taught to children. as a child i ALWAYS searched for this, never found it. no teacher ever knew what i was asking for. there was no internet like it is now back then. it wasnt until after college i actually indulged in critical thinking and studying it. the world would be a much better place if children would understand these terms.

[@ericstevens653]

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

[@NirangaDeSilva]

What will be the P(E | H) and P(E) values if we try out Sally and the flu example?

[@sandippatel5632]

great visuals and liked the simplicity of the explainations

[@svwingman7342]

Great video and easy to understand explanation. Thank you for creating.

[@TheNumbaOneMiss]

Philosophy was one of those subjects that I was SO excited to take in college! It started out smoothly until we started with these equations and I realized it's a lot like math, which I sucked at. I want so much to understand this stuff but it seems it really has to be B R O K E N all the way down for me in the simplest way. I love this stuff so much! Thanks for these videos!

[@stephenschumacher7876]

I have to ask a question that will be phrased somewhat awkwardly, so excuse me. If we view P(AlB) as stated, "The probability of A so long as the probability of B is 1," could we likewise make a weighted version of such a function where likelihood of B is increased to a number, call it P(B') ----> P(A)lP(B')=P(AlB)(1-(P(B)-P(B'))? Have I made a mistake somewhere or does this exist to be true?

[@2.0_two5]

I have an exam in a matter of hours. You saved me! thank you:)

[@promise7407]

How’d you do?

[@2.0_two5]

@@promise7407 I did really well, thank you!!

[@christianlibertarian5488]

Outstanding! Thanks for the help.

[@IvanHindrawan]

my professor used this video !, wonderful

[@timothyjamison8172]

How is P(H) discovered? How do they know how common Hypothesitis is in the general population? Especially since no test for Hypothesitis is 100% accurate. Is the data collected via autopsies?

[@JustineCarissa]

Excellent video! Thank you for breaking it down!!!

[@ruvstof]

Excelemt! it is the clearest explanation for me.

[@NIGHTMINER22]

What software did you use to create this?

[@p.z.8355]

if the syntoms are cleary visible shoudnt p(e|h) be 1 ? if you see its very likely to get a dripy nose and headache shouldnt p(e) be high ?

[@brightgardenentrepreneuria910]

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

[@praneetjoshi8541]

That's a really good explanation. Thank you!

[@somasundaram5573]

Excellent and clear cut explanantion . Thanks

[@PathakTutorials]

wow ... good method to teach wireless philosophy.

[@chetna1234]

You explained it really well ..

[@amdreallyfast]

I don't know why, but something of the wording in this explanation made it click for me. I think that it was using the term "evidence" instead of event. In explanations that I've heard previously, I was confused why we were dividing by the probability of an event occurring when the problem setup said explicitly that we don't know how often it occurs. The term "evidence" made more sense.

[@EdoardoMarcora]

hands down the easiest to understand video about the Bayes theorem

[@maraoz]

I watch all your videos and love them, thanks! I have some feedback though: Can you please tune down the intro effect volume? It's always too loud!

[@JATR1X]

what if the resulting probability after the calculation is greater than one, is this valid?

[@ramanujamveda1928]

Found the video really useful Explanation was really good.

[@jennifergreggs750]

Incredibly helpful - thank you!

[@SS-da1onder]

An awesome video, very clear and concise!

[@abdurhamzah9951]

Thanks very much for fantastic explanation :)

[@sarahpl2713]

Very well explained and clear thanks

[@equinoxhera5086]

thanks for the vid. i need this for my demo teaching

[@jeffreybagwell4421]

Thanks, that was admirably clear and concise!

[@harineemosur6530]

Beautifully done video

[@youtp007]

Really useful. Excellent video

[@JanusKannuberg]

Thanks for the clear explanation :)

[@jeffreydavidgoldberg8696]

i love the comments here.....very thought provoking

[@markerenberg3439]

This is a perfect explanation!

[@nathanchoi3763]

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?

[@rachelannezaragoza5855]

First video I finally understood!!

[@RafalSB]

Excellent approach. Thank You!

[@ahmedaj2000]

This made me comprehend it more, thank you!

[@VenkateshMogili]

Thank you for sharing, this is a nice video.....

[@primalpickle]

If Pr(e) is the probability of having symptoms, and you know you do have symptoms, isn't this value = 1 in your own case?

[@sjysong]

thanks it is so insightful to know this theorem

[@brendantannam499]

That was terrific. Thank you very much!

[@katrinajohnson2841]

Thank you for the excellent explanation!

[@phalienix]

i felt the explanations were very intuitive because the probabilities in the example were very plausible

[@KunalUpadhyay11]

superb illustration....

[@Mad.E]

Hey so I know this doesn't make any sense but I'm stumped: Looking at 2:07 If there are 15 boys in the class, isn't the probability of the patient being a boy 15/20 or 3/4? And then Sally has a 0% probability of being the patient. And the patient being a girl is 5/20 or 1/4. Where Sally would have a 1/5 or 20% chance of being the patient. But doesn't that mean that Sally's chance of being the patient is actually just (3/4 * 0) + (1/4 * 1/2) = 1/8 when following an imaginary tree diagram?

[@pantsharad]

Thanks man, you very well explained it , thanks a lot.

[@paradigmarson9586]

Hardest one in the series yet, but well explained.

[@SumitKumar-sp7ku]

awesome .. explanation take a bow

[@tausal1]

This is really helpful. Thank you!

[@MissBlossom02]

Sorry I'm stupid, how did he come up with 0.95 for P(E|H) ?

[@inevitabledeath]

I didn't get that either.

[@mythicallion780]

MissBlossom its just an example

[@CoryRauch]

If you have the illness (H) there is a 95% chance of exhibiting the symptoms (E). Inversely there is a 5% chance of having the illness and not exhibiting the symptoms. That number comes from the observed probabilities in the known population of those afflicted with the illness. ie. of the 100 people known to have the illness 95 of them display symptoms while 5 of them do not. Probability of the Symptoms given the Hypothesis. How likely is it that a person with hypothesitis would display the symptoms.

[@inevitabledeath]

Ya. I understood it just 5 seconds after typing my comment. Thanks anyway, the explanation may still be helpful for other viewers.

[@brandonhubah7278]

this makes a lot of sense. thx

Just awesome! Thanks a lot!

[@muthuksubramanian4143]

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

[@RekzaFS]

But how is it "given your symtoms" if you need to add the probability of having the symptons in the first place? That seems irrelevant to me since you already know you have the symptons, you don't need to look that up from a statistic, what you don't know is whether or not you have hypothetisis

[@gzpo]

Very cool, thanks!

[@ocel12356]

Very good video!

[@asddsa8203]

This is amazing.

[@6557myrs]

fantastic video

[@nigeljohnson9820]

Isn't it possible to visualise Bayes theorem using a Venn diagram?

[@millionairesclubllc3193]

If not, we can visualize it on yo momma instead

[@nigeljohnson9820]

@@millionairesclubllc3193 given that I am older enough to be your grandfather, I doubt if you have sufficient imagination. Must be so frustrating lacking both the imagination and the equipment necessary.

[@cliffordhodge1449]

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?

[@anqidai940]

This is great. Thank you!

[@ru_by_ru_by]

Great video, thanks!

[@anvarbeymuminov2785]

Nice man. God bless you

[@SJ-bz8ue]

Poor explanation, they didn't discuss the science behind derivation of the theorem

[@brooklynpublicphilosophers6204]

+Sj Sj Yeah, it would have been nice to go into that, and into interpretations of probability in more detail. Explaining and motivating the definition of conditional probability is hard, though; I think I would have lost more people than I needed to to get the basic point across. Maybe in a future video on conditionalization or Dutch Book arguments!

[@SJ-bz8ue]

Sure sir

[@effortless35]

+Brooklyn Public Philosophers What you need is a few basic examples where you can get conditional probabilities by pure counting as well as Bayes' theorem. The webMD example isn't bad but even better is something like testing for diseases with type A and type B errors. Ultimately, unless someone has a lot of experience with abstract math you need to give examples and show how changing different terms influences the result. In this example observing the symptoms made it far more likely that we had the disease. But the a priori probability was so low that even making it 10 times as likely didn't make much of a difference. BTW, I find the half-whimsical examples common in philosophy textbooks more annoying than illuminating. Better to use a simplified real world example or something plain like picking coloured balls from bags. Maybe it's just me though.

[@brooklynpublicphilosophers6204]

+effortless35 Yeah, more examples of the sort you describe would definitely help. I made a guess about what would be the best way of motivating and introducing Bayes' theorem in six minutes, but hopefully this encourages people to go find out more about probability theory, and they could work out whatever confusions linger as a result of watching the video then. For what it's worth, I actually don't think this is a whimsical example. Ordinary hypochondriacs and medical professionals fall prey to the base-rate fallacy all the time, so it seemed like a good way to demonstrate the real-world applicability of the theorem.

[@effortless35]

Brooklyn Public Philosophers I agree that it's an important example I just think using "hypothysis" is more distracting than illuminating. The example I've seen was testing tourists who return from Africa for tropical disease and it felt much more natural. Then again, it's just a personal thing and it might not generalize to your other viewers.

[@MrChatmoon]

Excellent !!!