Modern Probability Theory and Its Applications
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Modern Probability Theory and Its Applications

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Description

Mathematical probability theory is especially interesting to scientists and engineers. This work introduces probability theory, showing how probability problems can be formulated mathematically in order to systematically attack routine methods. Topics include independence and dependence probability laws and random variables. Over 500 exercises, an appendix of tables, and answers to odd-numbered questions are also included.
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Product details

  • Paperback | 480 pages
  • 155 x 229 x 29mm | 734g
  • John Wiley & Sons Inc
  • New York, United States
  • English
  • Wiley Classics Lib ed.
  • 0471572780
  • 9780471572787

Table of contents

Probability Theory as the Study of Mathematical Models of Random Phenomena. Basic Probability Theory. Independence and Dependence. Numerical-Valued Random Phenomena. Mean and Variance of a Probability Law. Normal, Poisson, and Related Probability Laws. Random Variables. Expectation of a Random Variable. Sums of Independent Random Variables. Sequences of Random Variables. Tables. Answers to Odd-Numbered Exercises. Index.
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About Emanuel Parzen

Emanuel Parzen was an American statistician. He worked and published on signal detection theory and time series analysis, where he pioneered the use of kernel density estimation. Parzen was the recipient of the 1994 Samuel S. Wilks Memorial Medal of the American Statistical Association.
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