Bayes probability
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Uploaded by profribasmat14x on Nov 16, 2009
simple tree method for Bayesian probability
- 107 likes, 1 dislikes
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Thank you, great video!
majorendre 3 weeks ago
thanx
magomah1 3 months ago
@shameelfaraz Because it's 92% of the 10% that have it. So take 10% of the population, then take 92% of that small group. e.g. population of 1,000,000 people, take 10%, that's 100,000 who have the disease. Then of those, take 92%, which is 92,000 who get detected (population x .10 x .92) , which leaves 8000 who don't get detected (pop x .10 * .08).
danielearwicker 3 months ago
@wangstick
you need to start with 67/33 rather than 10/90 and follow same steps you increase the probability from 67% to 97.4% you have the disease if you test positive twice in a row!!.
1960sadm 3 months ago
I have a question. Say you get tested 2 times. Intuitively, I would think the probability of, say, being positive and having it would increase substantially. But when I do the math by this same prob. tree method, I end up getting the same probabilities. What is the correct way of doing this? Or do the probabilities just not change no matter how many tests?
wangstick 3 months ago
I just wish i had seen this before. I was over the formula for quite some time without understanding it. This is by far the best method to do it, and its how I did it. Thanks for posting, this will help a lot of people. For anyone who wants to go even further, I suggest to investigate on Bayesian Networks (things get really complex down there).
Khullah 4 months ago
you tested negative, what is the probability of you not having the disease: 0.914
nabecaydim 4 months ago
thank you
hicelina 4 months ago
Thank you so much for explaining this intuitively! Now I actually understand how to use it.
mastersgta1 4 months ago
great help! :D
Emjhey12 7 months ago