Applied Probability (Springer Texts in Statistics)
| Author | : | |
| Rating | : | 4.38 (532 Votes) |
| Asin | : | 1441971645 |
| Format Type | : | paperback |
| Number of Pages | : | 436 Pages |
| Publish Date | : | 2015-11-07 |
| Language | : | English |
DESCRIPTION:
… one important feature of this edition is that it includes a more extensive list of exercises. I think both instructors and students will appreciate this welcome addition. From the reviews of the second edition:“Like the first edition, the new edition presents additional probability background material with applications to graduate students studying mathematical statistics, mathematical biology, engineering and applied mathematics. … A large number of exercises, many of which are newly included in this edition, facilitates the usage of the book for teaching purposes.” (Thorsten Dickhaus, Zentralblatt MATH, Vol. 53 (1), February, 2011)“This text contributes to bridging the increasing gap between sophisticated mathematical themes in probability theory and pragmatic, app
"good reference book" according to touchpiano. It is a really good reference book for graduate student in statistics. It covers almost all aspects of application of probablity theory and gives good examples as well. Worthy to have one.. Logical and concise A Customer I took Ken Lange's course while he was writing this book. It is an excellent book on applied probability and rather densely packed. The text assumes a background in basic probability theory but it is otherwise self-contained with clear and logical development of each topic. The examples motivate and explain the theoretical development.. Fazul said Packed with interesting information. If probability theory tickles your fancy at all, this is a really great reference to have. My only criticism is that, at times, the book reads like just a collection of results. But it is mostly very inspirational and informative.
Applied Probability presents a unique blend of theory and applications, with special emphasis on mathematical modeling, computational techniques, and examples from the biological sciences. Chapters 4 and 5 touch on combinatorics and combinatorial optimization. Chapter 3 deals with probabilistic applications of convexity, inequalities, and optimization theory. Chapter 1 reviews elementary probability and provides a brief survey of relevant results from measure theory. Chapter 2 is an extended essay on calculating expectations. If supplemented with a
Springer previously published his books Mathematical and Statistical Methods for Genetic Analysis, 2nd ed., Numerical Analysis for Statisticians, 2nd ed., and Optimization. He has written over 200 research papers and produced with his UCLA colleague Eric Sobel the computer program Mendel, widely used in statistical genetics. . Kenneth Lange is the Rosenfeld Professor of Compu