Question

What's the different between bayes's theorem and conditional theorem ?

Answer 1

Conditional Theorem:

Conditional Probability is the probability of a certain event (A) based on the occurrence of some other event (B). Mathematically it is represented as following:

P(A|B) = P(A∩B)/P(B)

here, the LHS is the conditional probability we aim to calculate(P(A|B)) by dividing the probability of both events in question occurring together (P(A∩B)) with the probability of the event assumed to have already occurred (P(B)).

Bayes Theorem:

Bayes theorem is an extension of conditional probability. While using Bayes theorem you use one conditional probability to calculate another one. Bayes theorem is represented with the following expression:

P(A|B) = P(B|A) * P(A)/P(B)

here, we calculate the probability of event A given that event B has occurred. The RHS consists of the probability of event B given event A has occurred multiplied by the ratio of probability of event A to Probability of event B.