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Conditional Probability and Independence

  • Anirban DasGupta
Chapter
Part of the Springer Texts in Statistics book series (STS)

Abstract

Both conditional probability and independence are fundamental concepts for probabilists and statisticians alike. Conditional probabilities correspond to updating one’s beliefs when new information becomes available, a natural human instinct. Independence corresponds to irrelevance of a piece of new information, even when it is made available. Additionally, the assumption of independence can and does significantly simplify development, mathematical analysis, and justification of tools and procedures. Indeed, nearly every key result in probability and statistics was first derived under suitable independence assumptions and then extended to selected cases where independence may be lacking. These two topics together also provide the reader with a supply of fascinating problems and often very pretty solutions.

Keywords

Conditional Probability Independent Event Sample Space Slot Machine Defective Item 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York 2010

Authors and Affiliations

  1. 1.Dept. Statistics & MathematicsPurdue UniversityWest LafayetteUSA

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