On overview and two examples of Bayes' Theorem in the context of decision trees.
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@bytemoney5655 Жыл бұрын
its always the people who have a pen and paper setup that will save your life thank you very much
@RichardRuoro6 жыл бұрын
Great lesson but on the probability that someone with side effects is male, there seems to an error. The problem comes in when you calculate P(E|S) this should come to 0.07 and not 0.065. Also 0.2*0.7/0.41 = 0.341 and not 0.659 Please correct me if am wrong?
@quantquill6 жыл бұрын
I agree, good video, good demonstration of decision trees, and both of these problems have typos. In the first one, the intermediate typo of 0.065 (should be 0.07) throws off the final answers, which should be: P(male | side effects) = .429 (and P(female| side effects) = .571). In the second problem, everything is correct right up to the end. I believe the answer given is for P(Weak market|negative results of market research) = 0.659, rather than P(Strong market|negative results of market research), which is 0.341.
@anthony365935 жыл бұрын
Your totally right answer is .07 or 7% chance
@qualquan4 жыл бұрын
probability of being male is 3/7 = 42.85% by my reckoning
@wongpeisan20733 жыл бұрын
AGREE
@ideastmf2 жыл бұрын
@@quantquill that’s true👍
@jackrubin63033 жыл бұрын
In your first example (0.1x0.4) + (0.05x0.6) = 0.07 not 0.065. In your second example (0.2x0.7)/0.41 = 0.3415 not what you calculate
@greatstoneface51373 ай бұрын
You are right!
@agapaojumba96512 жыл бұрын
Wonderful presentation. I have understood well the Bayes' Theorem
@74descartes4 жыл бұрын
Well done you have a real knack for that.
@richardgordon2 жыл бұрын
I love this video😍. By far the best explanation of how to figure out Bayesian’ theorem.
@mohamedabdou-salamiАй бұрын
I totally agree with you. Watched so many videos, but this nailed it for me. Thank you from Zambia.❤
@somdubey54366 жыл бұрын
thanks for the quality understanding for Bayes Theorem.
@qualquan4 жыл бұрын
I calculate the probability of being male as 3/7 = 42.86%
@EmperorsNewWardrobe2 жыл бұрын
Yup, the P(SE) should have come to 0.07, not 0.065
@jim2376 Жыл бұрын
@@EmperorsNewWardrobe Correct.
@princessronaalcantara65932 жыл бұрын
I like your strategy ❤️ thank you!
@user-jd8ms6qb8d5 ай бұрын
Thanks for this very helpful lesson. Please make more videos on probability. Your explanations are easy to understand
@jacquelinesamuda65476 жыл бұрын
Excellent presentation. It actually makes sesne with the diagrams'
@danteconciatori10942 жыл бұрын
positive should be 90% and negative should be 10% for the market question
@aswinimechiri3157Ай бұрын
extraordinary explanation mam...thank you.
@taufiquddikhan11683 жыл бұрын
Indeed, this is a great help to teachers of Mathematics.
@aashayshirodkar3 жыл бұрын
Hi, Thank you very much. This helped me resolving my doubts.. Aashay S. (India 🇮🇳 )
@ahmed.bhewary7754 жыл бұрын
thanks it was useful ... good job .. keep up the good working
@kebman2 жыл бұрын
Node 0: Market State Edge 0.0 Strong: 70% → Node 0.0 Research Result → Edge 0.0.0 Positive: 80% → Edge 0.0.1 Negative: 20% Edge 0.1 Weak: 30% → Node 0.1 Research Result → Edge 0.1.0 Positive: 10% → Edge 0.1.1 Negative: 90% The probability for a positive result: P(+) Is the combination of the branches that contain “positive” in the original tree. So in other words: Edge 0.0 Strong: 70% → Edge 0.0.0 Positive: 80% and Edge 0.1 Weak: 30% → Edge 0.1.0 Positive: 10% Applying the denominator of Bayes' Theorem: Positive: P(A|B)P(B) + P(A|!B)P(!B) ⇒ P(+|S)P(S) + P(+|W)P(W) ⇒ P(0.8)P(0.7) + P(0.1)P(0.3) ⇒ (0.8)(0.7)+(0.1)(0.3) ⇒ 0.59 = 59% And thus we automatically know the answer to negative being 41%. P(S|+) = P(+|S)P(S) / P(+) ⇒ P(S|+) = P(0.8)P(0.7) / P(0.59) ⇒ P(S|+) = (0.8)(0.7) / (0.59) ⇒ 0.949152542 ≈ 0.95 P(S|-) = P(-|S)P(S) / P(-) ⇒ P(S|-) = P(0.2)P(0.7) / P(0.41) ⇒ P(S|-) = (0.2)(0.7) / (0.41) ⇒ 0.341463415 ≈ 0.34 Node 0: Research Result Edge 0.0: Positive: 59% → Node 0.0 Market State → Edge 0.0.0 Strong: 95% → Edge 0.0.1 Weak: 5% Edge 0.1: Negative: 41% → Node 0.1 Market State → Edge 0.1.0 Strong: 34% → Edge 0.1.1 Weak: 66%
@esonanakani579 Жыл бұрын
I think there is a problem on the second example, the first tree diagram, the weak part (percentages of indicating and not indicating)
@cecileboulanger61036 жыл бұрын
Very very helpful thanks :-)
@dhatridongre88496 жыл бұрын
I still don't understand why does the probability change when direction is reversed. Someone please help???
@BANKO007 Жыл бұрын
Excellent explanation from first principles that is much better than most, which treat Bayes as a black box formula. Good also that the answer is scientifically accurate wrt gender. Imagine the contortions necessary if sex was arbitrary and based on self-identification? Statistics would be meaningless if sex were treated as a fiction.
@sanazghobadi93914 жыл бұрын
really helpful, thank you so much for this amazing presentation
@harukatakagi61416 жыл бұрын
When it says in the problem, "if the market was weak there is a 90% chance the research would indicate so" wouldn't that mean that the probability of it being weak and positive would be 90%? However it says 10% in your first diagram. Maybe I am just stupid, but that doesn't make much sense to me. Is it just an error in the calculations?
@ahmadataei703 жыл бұрын
I thought the same! I think you are right!
@kshitijchhajed32422 жыл бұрын
I have the same question! @Doulton Wiltshire, Could you please check?
@ExistentialGojora Жыл бұрын
If you follow the tree diagram strategy from the first part, than the sum total of all "positive results" seems to mean that the denominator would be: P(All Correct Research Results) = P(Correct|Strong) P(Strong) + P(Correct|Weak) P(Weak) =.80(.70) + .90(.30) = .56 + .27 = .83 At least that's what I think it should be. Maybe that's why I'm struggling with this subject.
@abelbeliyu35416 ай бұрын
for your surprise I was thought the same and looking for comments for confirmation
@JobGathirufisher Жыл бұрын
This was really helpful.
@debiprasadpanda13956 жыл бұрын
LOVELY.
@bazooka57803 жыл бұрын
YOU ARE A HERO not a TEACHER MISS XD
@dwivedys5 ай бұрын
Using Baye’s theorem: P(M|SE) = P(SE|M) * P(M) / (P(SE|M)*P(M) + P(SE|F)* P(F)) --- (1) = 5%*60%/(5%*60% + 4%* 10%) = 3%/7% = 0.42857 or 42.86% is the probability that someone is male given that someone is showing a side effect. Let’s break it down: What % of overall population shows side effect? That is 10% of 40% females = 4% and 5% of 60% males = 3%. So this is total 7%. This is what goes in the denominator of (1) above: P(SE) = P(SE|M)* P(M) + P(SE|F)* P(F). Allow me to take another shot at explaining this without losing our heads in all the formulas. ‘ You have a set of males and females (in a gender binary world). 40% females and 60% males. Of the 40% females 10% have SE. So how many females with SE? 10% of 40% = 4% Similarly how many males with SE? It is given 60% of population is males and 5% of them have SE so 5% * 60% = 3%. So right there you have 3% + 4% = 7% of the overall population that’s showing SE. How many of them is males? We know already that is 5% * 60% = 3%. So of the 7% actually 3% are males. So that’s 3% / 7% or 42.86% is the answer That 3% + 4% is actually the denominator P(SE|M) * P(M) + P(SE|F) * P(F) And 3% is simply P(SE|M) * P(M)
@janendonye16392 жыл бұрын
P(a tutorial from you is awesome)=1
@salemal-esawi43054 жыл бұрын
thank you
@leomcpie7904 Жыл бұрын
BTW ATTENTION: THE PROBABILITY OF P(SE) IS NOT 0.065 BUT 0.07!
@kroneraram5 жыл бұрын
Got 42.86% (!?) in the first problem: 0.03/0.0.3+0.04=0.4285714
@qualquan4 жыл бұрын
agree
@uthpakhi2 жыл бұрын
Thanks
@kebman2 жыл бұрын
A' = nought A or not A? Or nawt A??? With programming we'd say either !A or A = 0 (not A and naught A respectively). Edit: Nevermind. I now see that it's "Not A" ^^
@simonndungu97464 жыл бұрын
From past experience it is known that a machine if set up correctly 90% of the time, then 95% of good parts are expected but if the machine is not set up correctly then the probability of a good part is only 30%. On a given day the machine is set up and the first component produced was found to be good. What is the probability that the machine is set up correctly?
@samore112 жыл бұрын
Your P(SE) should be .07, not .065. The final answer is 3/7 = .429
@kopanomoss57522 жыл бұрын
nice
@vincentkaapehi60462 ай бұрын
The second question confusing!! We don’t even know what we are being ask to look for?? You just started answering
@jim23766 ай бұрын
The answer is 42.85% probability not 46.15%.
@godfidence1Ай бұрын
The presentation is appreciated but the calculation in the first question is way too off.. still good efforts!
@lukel42976 жыл бұрын
First!
@erickkadoh77727 күн бұрын
Your explanation is very confusing...go and check how @organic chemistry tutor presents
@princechidebe30679 ай бұрын
I love the way u teach ma'am 🥹. I understand everything. Much love ❤️