Introduction to Applied Probability

Released on by Paul E. Pfeiffer
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  • Introduction to Applied Probability Book Detail

  • Author : Paul E. Pfeiffer
  • Release Date : 2014-05-10
  • Publisher : Elsevier
  • Genre : Mathematics
  • Pages : 420
  • ISBN 13 : 1483277208
  • File Size : 14,14 MB
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Introduction to Applied Probability by Paul E. Pfeiffer PDF Summary

Book Description: Introduction to Applied Probability provides a basis for an intelligent application of probability ideas to a wide variety of phenomena for which it is suitable. It is intended as a tool for learning and seeks to point out and emphasize significant facts and interpretations which are frequently overlooked or confused by the beginner. The book covers more than enough material for a one semester course, enhancing the value of the book as a reference for the student. Notable features of the book are: the systematic handling of combinations of events (Section 3-5); extensive use of the mass concept as an aid to visualization; an unusually careful treatment of conditional probability, independence, and conditional independence (Section 6-4); the resulting clarification facilitates the formulation of many applied problems; the emphasis on events determined by random variables, which gives unity and clarity to many topics important for interpretation; and the utilization of the indicator function, both as a tool for dealing with events and as a notational device in the handling of random variables. Students of mathematics, engineering, biological and physical sciences will find the text highly useful.

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Introduction to Applied Probability

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Introduction to Applied Probability provides a basis for an intelligent application of probability ideas to a wide variety of phenomena for which it is suitable

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Despite the fears of university mathematics departments, mathematics educat,ion is growing rather than declining. But the truth of the matter is that the increa

An Introduction to Applied Probability

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Designed for a curriculum that contains only 2 single one-semester course on probability. Covers the core of probability theory, considers sums of random variab