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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Conditional Independence in Applied Probability

Conditional Independence in Applied Probability

Pfeiffer, P. E.

Paperback

Series: Modules and Monographs in Undergraduate Mathematics and Its

General ReferenceGeneral GardeningGeneral Science

ISBN10: 1461263379
ISBN13: 9781461263371
Publisher: Springer Nature
Published: Nov 9 2011
Pages: 158
Weight: 0.44
Height: 0.36 Width: 5.50 Depth: 8.50
Language: English
It would be difficult to overestimate the importance of stochastic independence in both the theoretical development and the practical appli- cations of mathematical probability. The concept is grounded in the idea that one event does not condition another, in the sense that occurrence of one does not affect the likelihood of the occurrence of the other. This leads to a formulation of the independence condition in terms of a simple product rule, which is amazingly successful in capturing the essential ideas of independence. However, there are many patterns of conditioning encountered in practice which give rise to quasi independence conditions. Explicit and precise incorporation of these into the theory is needed in order to make the most effective use of probability as a model for behavioral and physical systems. We examine two concepts of conditional independence. The first concept is quite simple, utilizing very elementary aspects of probability theory. Only algebraic operations are required to obtain quite important and useful new results, and to clear up many ambiguities and obscurities in the literature.

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