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What is the difference between independent and conditional probability? give an example of each. Which one requires the use of addition rule?
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Independent events have no effect on the occurrence (or non-occurrence) of each other. Events A and B are independent if, and only if\[\large P(A\cap B)=P(A) \times P(B)\] Also A and B are independent if \[\large P(A|B)=P(A)\] and \[\large P(B|A)=P(B)\]
Conditional probability is the probability of an event occurring given that another event has already occurred. The conditional probability of A occurring, given that B has occurred, is written P(A|B). The formula for conditional probability is \[\large P(A|B)=\frac{P(A\cap B}{P(B)}\]
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