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1974
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.
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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.
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Selective Influence Through Conditional Independence
Psychometrika, 2003Let each of several (generally interdependent) random vectors, taken separately, be influenced by a particular set of external factors. Under what kind of the joint dependence of these vectors on the union of these factor sets can one say that each vector is selectively influenced by “its own” factor set?
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A genome-wide transgenic RNAi library for conditional gene inactivation in Drosophila
Nature, 2007Frank Schnorrer +2 more
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A conditional knockout resource for the genome-wide study of mouse gene function
Nature, 2011Jennifer Harrow +2 more
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Conditional mouse models of sporadic cancer
Nature Reviews Cancer, 2002Jos Jonkers, Anton Berns
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