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Question

What is the difference between conditional probability and Bayes Theorem?


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Solution

Difference between conditional probability and Bayes Theorem:

The differences between conditional probability and Bayes Theorem are tabulated as follows:

S. No.

Conditional Probability

Bayes Theorem

1.Conditional Probability is the probability of occurrence of a certain event, say A, based on some other event B which has already occurred.Bayes Theorem includes two conditional probabilities for the events, say A and B.
2.

The equation of conditional probability is:

P(A|B)=P(AB)P(B)

The equation of Bayes Theorem is:

P(A|B)=P(B|A)×P(A)P(B)

3.It is used to compute the conditional probability and the events Aand B are relatively simple.It is used in Bayesian inference and in models where we are interested in the distribution up to a normalizing factor P(B)
4.It is used for relatively simple problemsIt gives a structured formula for solving more complex problems.

Hence, the differences between conditional probability and Bayes theorem are stated above.


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