Explanation:
Independence (probability theory)
In probability
theory, to say that two events are independent intuitively means that the occurrence of one event makes it
neither more nor less probable that the other occurs For
example:
1. The
event of getting a 6 the first time a die is rolled and the event of getting a
6 the second time are independent.
2. By
contrast, the event of getting a 6 the first time a die is rolled and the event
that the sum of the numbers seen on the first and second trials is 8 are not independent.
3. If two
cards are drawn with replacement from a deck of cards, the
event of drawing a red card on the first trial and that of drawing a red card
on the second trial are independent.
4. By
contrast, if two cards are drawn without replacement from a
deck of cards, the event of drawing a red card on the first trial and that of
drawing a red card on the second trial are again not independent.
Similarly, two random
variables are independent if the
conditional probability distribution of either given the observed value of the
other is the same as if the other's value had not been observed. The concept of
independence extends to dealing with collections of more than two events or
random variables.
In some instances, the term "independent" is replaced by
"statistically independent", "marginally independent",
or "absolutely independent".
Independent
events
The standard
definition says:
Two events A and B are independent if and only if Pr(A ∩ B) = Pr(A)Pr(B).
Here A ∩ B is the intersection of A and B, that is, it is the event
that both events A and B occur.(Our solved example in
mathguru.com uses this concept)
http://en.wikipedia.org/wiki/Independence_(probability_theory)#Independent_events
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