Conditioning and Independence

  • Kai Lai Chung
Part of the Undergraduate Texts in Mathematics book series (UTM)


We have seen that the probability of a set A is its weighted proportion relative to the sample space Ω. When Ω is finite and all sample points have the same weight (therefore equally likely), then
$$ P\left( A \right) = \frac{{\left| A \right|}}{{\left| \Omega \right|}} $$
as in Example 4 of §2.2. When Ω is countable and each point ω has the weight P(ω) = P({ω}) attached to it, then
$$ P\left( A \right) = \frac{{\sum\limits_{\omega \in A} {P\left( \omega \right)} }}{{\sum\limits_{\omega \in \Omega } {P\left( \omega \right)} }} $$
from (2.4.3), since the denominator above is equal to 1. In many questions we are interested in the proportional weight of one set A relative to another set S. More accurately stated, this means the proportional weight of the part of A in S, namely the intersection A ∩ S, or AS, relative to S. The formula analogous to (5.1.1) is then
$$ \frac{{\sum\limits_{\omega \in AS} {P\left( \omega \right)} }}{{\sum\limits_{\omega \in S} {P\left( \omega \right)} }} $$
Thus we are switching our attention from Ω to S as a new universe, and considering a new proportion or probability with respect to it. We introduce the notation
$$ P\left( {A\left| S \right.} \right) = \frac{{P\left( {AS} \right)}}{{P\left( S \right)}} $$
and call it the conditional probability of A relative to S. Other phrases such as “given S,” “knowing S,” or “under the hypothesis [of] S” may also be used to describe this relativity.


Black Ball Conditional Probability Independent Random Variable General Random Variable Apriori Probability 
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Copyright information

© Springer-Verlag New York Inc. 1979

Authors and Affiliations

  • Kai Lai Chung
    • 1
  1. 1.Department of MathematicsStanford UniversityStanfordUSA

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