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Verification of this far reaching result rests on the minterm expansion and two elementary facts about the disjoint subclasses of an independent class. We state these facts andconsider in each case an example which exhibits the essential structure. Formulation of the general result, in each case, is simply a matter of careful use of notation.
Consider the independent class , with respective probabilities 0.4, 0.7, 0.3, 0.5, 0.8, 0.3, 0.6. Consider M 3 , minterm three for the class , and N 5 , minterm five for the class . Then
Also
The product rule shows the desired independence.
Again, it should be apparent that the result holds for any number of A i and B j ; and it can be extended to any number of distinct subclasses of an independent class.
Suppose and , with independent for each pair . Suppose
We wish to show that the pair is independent; i.e., the product rule holds.
COMPUTATION
Now
By additivity and pairwise independence, we have
The product rule can also be established algebraically from the expression for , as follows:
It should be clear that the pattern just illustrated can be extended to the general case. If
then the pair is independent. Also, we may extend this rule to the triple
and similarly for any finite number of such combinations, so that the second proposition holds.
To illustrate, we return to [link] , which involves an independent class of ten events.
Consider again the independent class with respective probabilities . We wish to calculate
In the previous solution, we use minprob to calculate the minterms for all ten of the E i and determine the minterm vector for F . As we note in the alternate expansion of F ,
We may calculate directly . Now A is a Boolean combination of and B is a combination of . By the result on independence of Boolean combinations, the class is independent. We use the m-procedures to calculate and . Then we deal with the independent class to obtain the probability of F .
>>p = 0.01*[13 37 12 56 33 71 22 43 57 31];>>pa = p([1 3 4 7]); % Selection of probabilities for A>>pb = p([2 5 6 8]); % Selection of probabilities for B>>pma = minprob(pa); % Minterm probabilities for calculating P(A)>>pmb = minprob(pb); % Minterm probabilities for calculating P(B)>>minvec4;>>a = A|(B&(C|Dc)); % A corresponds to E1, B to E3, C to E4, D to E7>>PA = a*pma'
PA = 0.2243>>b = A&(Bc|(C&D)); % A corresponds to E2, B to E5, C to E6, D to E8>>PB = b*pmb'
PB = 0.2852>>PC = p(9)*(1 - p(10))
PC = 0.3933>>pm = minprob([PA PB PC]);>>minvec3 % The problem becomes a three variable problem>>F = A|B|C; % with {A,B,C} an independent class>>PF = F*pm'
PF = 0.6636 % Agrees with the result of
[link]
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