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bhathi123
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P(S1 [itex]\cap[/itex] S2 [itex]\cap[/itex] S3 | r)
How do I simplfy the above equation if S2 and S3 are independent of r ?
How do I simplfy the above equation if S2 and S3 are independent of r ?
Conditional probability is the likelihood of an event occurring given that another event has already occurred. In science, conditional probability allows us to make more accurate predictions and understand the relationships between different variables.
Conditional probability is calculated by dividing the probability of the joint event (both events occurring) by the probability of the first event. This can be represented as P(A|B) = P(A and B) / P(B).
Unconditional probability is the likelihood of an event occurring without any prior knowledge or conditions. Conditional probability takes into account a specific condition or event that has already occurred and adjusts the probability accordingly.
One example of conditional probability in science is in medical testing. The likelihood of a patient having a certain disease may be different depending on whether they have a family history of the disease or not. The conditional probability of having the disease given a positive family history would be different from the unconditional probability of having the disease.
Conditional probability can be used to identify potential confounding variables in an experiment and adjust for them in the design. By understanding the relationships between variables, scientists can control for potential influences and increase the accuracy and reliability of their results.