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The idea of stochastic (probabilistic) independence is explored in the unit Independence of Events . The concept is approached as lack of conditioning: . This is equivalent to the product rule . We consider an extension to conditional independence.
Examination of the independence concept reveals two important mathematical facts:
This raises the question: is there a useful conditional independence—i.e., independence with respect to a conditional probability measure? In this chapter we explore thatquestion in a fruitful way.
Among the simple examples of “operational independence" in the unit on independence of events, which leadnaturally to an assumption of “probabilistic independence” are the following:
A department store has a nice stock of umbrellas. Two customers come into the store “independently.” Let A be the event the first buys an umbrella and B the event the second buys an umbrella. Normally, we should think the events form an independent pair. But consider the effect of weather on the purchases. Let C be the event the weather is rainy (i.e., is raining or threatening to rain). Now we should think and . The weather has a decided effect on the likelihood of buying an umbrella. But given the fact the weather is rainy(event C has occurred), it would seem reasonable that purchase of an umbrella by one should not affect the likelihood of such a purchase by the other. Thus,it may be reasonable to suppose
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