Probability and Statistics: Conditional Probability

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Conditional probability is the likelihood of an event occurring, assuming a different one has already happened. In this lecture, we are going to show you how to compute and interpret such probability.

Let’s go back to the coin flip example from last lecture. “A” represents getting heads and “B”
represents getting heads on the previous flip. The probability of getting heads now, after getting heads last time, is still 0.5. Therefore, P of A, equals P of, A given B. This is equivalent to saying the two events are independent. Earlier in the course we also mentioned that if any two events are independent, the probability of their intersection is the product of the individual probabilities.

Now, let us examine the Queen of Spades example from last lecture, where A represented drawing
that exact card, B represented drawing the correct suit and C represented getting a queen.

Normally, the probability of drawing the Queen of Spades is equal to 1 over 52. However, it increases if we know it’s a spade.

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At 5:10 shouldn't this be opposite of what he is saying, the probability of of a vegetarian being a woman is higher, so the likelihood for a vegetarian to be a female is higher than that of a woman being a vegetarian. Pls correct me if i m wrong

aryadubey
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this one reminds me of catholic church, i am dozing now

sylviasimasiku
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You got your genders mixed up there buddy...

freddyb
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Thanks for the upload, but I think your results on 5:00 is not based on your values on 4:30. If true, please correct your video

esanau
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u are the best, just u did an error at 4:56, check ur table for a correct values. good luck

irestaurant
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Good can anyone say how much probability topics are left

shiffin_chippe