Solid post! Nothing new, but a great refresher, especially of basic probability terminology.
Quote:
Originally Posted by DiamondDog
Sometimes we’ll be interested in two independent events. Events are said to be independent if the occurrence (or non occurrence) of one of them has no impact at all on the likelihood of the other occurring. For example if I spin a coin and roll a die, the result of the coin (Heads or Tails) is totally independent of the result of the die (1,2,3,4,5, or 6).
In sports ...
We have a simple rule for dealing with the probability of two independent events both happening:
p(A AND B) = p(A) x p(B)
So if I spin the coin and roll the die,
p(Heads AND 4)
= p(Heads) x p(4)
= 1/2 x 1/6
= 1/12
(exactly the result you’d get if you were to list all possible outcomes:
(H,1),(H,2) …. (T,5),(T,6)
a list of 12 outcomes, of which (H,4) is just one.)
Should mention that in your OP, p(Heart AND Ace) is a great poker example of two independent events! No need to turn to sports, dice or coins!
Because the suit you choose has no limitation on which ranks you can choose afterwards for the same card, we can say that p(Heart) and p(Ace) are
mutually independent of each other!
That is,
p(Heart AND Ace) = p(Heart) x p(Ace) = 1/4 x 1/13 = 1/52
Thus, p(Heart OR Ace) = p(Heart) + p(Ace) - p(Heart AND Ace) = p(Heart) + p(Ace) - p(Heart) x p(Ace)
Replacing Heart and Ace with general variables A, B:
p(A OR B) = p(A) + p(B) - p(A AND B) <- in general where A, B are any two events
p(A OR B) = p(A) + p(B) <- A, B are mutually exclusive: p(A AND B) = 0
p(A OR B) = p(A) + p(B) - p(A) x p(B) <- A, B are mutually independent: p(A AND B) = p(A) x p(B)
Note that two non-trivial events, p(A), p(B) not= 0, cannot be mutually exclusive and mutually independent simultaneously.
Thus, we can say for non-trivial events, exclusiveness implies dependence and inexclusiveness implies independence.
That is to say, the concepts of mutual exclusiveness and independence are, in fact, not independent.
Now, on to post #2!
Last edited by jzc; 04-03-2013 at 03:53 AM.