| Fundamentals of Statistics contains material of various lectures and courses of H. Lohninger on statistics, data analysis and chemometrics......click here for more. |

| See also: conditional probabilities | |
Independent EventsA and B are independent events if the occurrence of B does not influence the probability that A occurs, and vice versa: P(A|B) = P(A)
Experiments are usually (or should be) planned such that they are independent. Example:A coin is tossed twice and we define the events A{the 1st toss is a head} and B{the 2nd toss is a head}. Does the result of the first toss affect the result of the second toss? Intuitively, we would say 'No', but we want to prove it. NOTE
P(A Ç B) = P(A) . P(B) This can be derived from the equation P(A Ç B) = P(A) . P(B|A), where P(B|A) = P(B) when the events are independent. Independence of several eventsWhen ,
then all sub-events Ei are independent, too. A set of events
is independent if every finite subset of these events is independent, too.
Sometimes the probability of an experiment consists of a series of sub-experiments
(tossing coins several times, one toss). In many cases we can assume that
outcomes are independent. If all the experiments are identical and if the
experiments have the same sample space and probability, we speak of trials.
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