NATURE.M said:
Ok that makes more sense. Basically, we are solving for P(A ∪ B ∪ C) then. Taking your suggestions I can start by computing these simple probabilities like P(A or B) = P(A υ B) = P(A) + P(B) - P(A ∩ B). Similarly, P(A or C) = P(A) + P(C) - P(A ∩ C) and P(B or C) = P(B) + P(C) - P(B ∩ C).
And Ray Vickson do you mean find the probability of P(A and not B and not C) ?
And also can't i just express P(A ∪ B ∪ C) = P(A) + P(B) + P(C) - P(A∩B) - P(A∩C) - P(B∩C) +P(A∩B∩C) which was a theorem we discussed in class.
(i) Yes to your first question.
(ii) Yes, you can express P(A ##\cup## B ##\cup##C) as you have done, but that is NOT P(A only, or B only, or C only). That is why I tried to lead you gently to a solution, by asking you if you can express P(A only) in a similar way to what you have done above. Then, do the same for P(B only) and P(C only). The answer you seek is
P(exactly one of A,B,C) = P(A only) + P(B only) + P(C only),
because the events on the right are now mutually exclusive. Looking at a Venn diagram should help you a lot.
It turns out that there is a generalization of the inclusion-exclusion principle that allows for computation of things like
P\{\text{exactly}\; r \; \text{of the events} \; A_1, A_2, \ldots, A_n \; \text{occur} \}
in terms of the sums
\begin{array}{rcl}S_1 &=& \sum P(A_i), \\S_2 &=& \sum_{i < j} P(A_i A_j), \\S_3 &=& \sum_{i < j < k} P(A_i A_j A_k), \\ & \vdots &\\S_n &=& P(A_1 A_2 \cdots A_n)<br />
\end{array}
You can find it in the classic textbook W. Feller, "Introduction to Probability Theory and its Applications", Vol. 1, Wiley (1968), for example. Other textbooks, such as those of Sheldon Ross develop the same results in more "modern" (but IMHO more obscure and less enlightening) ways.
Note added in edit: is your problem really exactly as you wrote it in post #1? There you basically said "exactly one of the events occur", which is very different from "at least one of the events occur". The latter would be "A or B or C", but the former would not be.