This section introduces the main modeling concept behind the entries in the Table . A , B are independent, if the conditional probability is the same as unconditional, . In modeling it is often assumed rather than verified. For instance, we shall assume that the events generated by consecutive outputs of the random generator are independent.
Beginners sometimes confuse disjoint versus independent events.
Not compatible outcomes cannot happen at the same time. This is not the same as independent outcomes. If A , B are disjoint and you know that A occurred, then you do know a lot about B . Namely you know that B cannot occur. Thus there is an interaction between A and B .