In statistics, two events are *dependent* if the occurrence of one of the events causes the probability of the other event occurring to change in a predictable way.

*Bayes Theorem* calculates the probability of `A`

given `B`

as the probability of `B`

given `A`

multiplied by the probability of `A`

divided by the probability of `B`

:

`P(A|B)= {P(B|A)*P(A)}/{P(B)}`

This theory describes the probability of an event (`A`

), based on prior knowledge of conditions (`P(B|A)`

) that might be related to the event.

In statistics, two events are *independent* if the probability of one event occurring does not affect the probability of the second event occurring.