Introduction to Bayes’ Theorem
Bayes’ theorem sometimes called as Bayes’Law and Bayes’Rule is a theorem of probability that stated by Reverend Thomas Bayes. The theorem describes the probability of the event that based on some of the conditions that might be related to event. This theorem apply in wide variety of range, ranging from marine biology to the development of the spam folder for email system. The main purpose of the theorem is try to find out the relationship between theory and evidence. Now look at the theorem and the terminologies involved in it.
P(TE)=(P(E│T)×P(T))/(P(E│T)×P(T)+P(E│¬T)×P(¬T))
Here T stands for Theory that we are going to going to test, and E stands for evidence on this the theory depends either it seems to confirm or disallow. For any proposition we use P(S) where S should be true and here P(T) represents estimate of the probability that we are considering so we can call this as a prior probability of T. ¬T shows the negation of T that means proposition of T is false.

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