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Conditional probability


               PROOF. Let n be the total number of uniquely possible, equiprobable and incompatible outcomes; m a
               number of outcomes leading to the occurrence of the event A; l the number of outcomes leading to the
               occurrence of the event B and k the number of outcomes leading to the occurrence of both A and B. Then

                                                            k    km     m k
                                                 P(AB) =      =      =     ·  ,
                                                            n    nm     n   n

               but  m  = P(A),  k  = P A (B) and hence
                   n           m

                                                   P(AB) = P(A) · P A (B).

                   From (3.1) we obtain
                                                                P(A ∩ B)
                                                     P(A|B) =                                              (3.2)
                                                                  P(B)

               and
                                                                P(B ∩ A)
                                                    P(B|A) =              .                                (3.3)
                                                                  P(A)
               In terms of Venn diagrams, we may think of P(B|A) as the probability of B in the reduced sample
               space defined by A. Thus, if two events A and B are mutually exclusive then


                                                    P(A|B) = 0 = P(B|A).                                   (3.4)

                   It follows from (3.1) that the probability of joint appearance of any number of events is equal
               to the probability of one of them multiplied by: the conditional probability of another relative
               to the first event, the conditional probability of the third event relative to the intersection of two
               first events, etc. by the conditional probability of the last event relative to the intersection of all
               preceding ones:


                           P(A 1 A 1 . . . A n ) = P(A 1 )P(A 2 /A 1 )P(A 3 /A 1 A 2 ) . . . P(A n /A 1 A 2 . . . A n−1 ).  (3.5)

                   It is easy to see that conditional probabilities have properties analogous to those of ordinary
               probabilities. For example,

                  1. 0 ≤ P A (B) ≤ 1

                  2. If A and B are incompatible, so that AB = ∅, then P A (B) = ∅.

                  3. If A implies B, so that A ⊂ B then P A (B) = 1.

                   If the events A and B are independent then the probability for their product is defined by the
               formula
                                                     P(AB) = P(A)P(B).                                     (3.6)

               Example 3.2. The break in an electric circuit occurs when at least one out of
               three elements connected in series is out of order. Compute the probability that
               the break in the circuit will not occur if the elements may be out of order with
               the respective probabilities 0.3, 0.4 and 0.6. How does the probability change if
               the first element in never out of order?                                                       ,

               Solution. The required probability equals the probability that all three elements in series are
               working. Let A k (k = 1, 2, 3) denote the event that the k-th element functions. Then p =
               p(A) = P(A 1 A 2 A 3 ). Since the events may be assumed independent, p = P(A 1 ) = P(A 2 ) =
               P(A 3 ) = 0.7·0.6·0.4 = 0.168. If the first element is not out of order, then p = p(A 2 A 3 ) = 0.24.


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