Introduction to probability / David F. Anderson, University of Wisconsin, Madison, Timo Seppäläinen, University of Wisconsin, Madison, Benedek Valkó, University of Wisconsin, Madison.
By: Anderson, David F [author]
Contributor(s): Seppäläinen, Timo O [author] | Valkó, Benedek [author]
Language: English Series: Cambridge mathematical textbooksPublisher: Cambridge; New York : Cambridge University Press, 2018Description: xv, 429 pages ; 26 cmContent type: text Media type: unmediated Carrier type: volumeISBN: 9781108415859Subject(s): Probabilities -- TextbooksDDC classification: 519.2 LOC classification: QA273 | .A5534 2018Summary: This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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GRADUATE LIBRARY | GRADUATE LIBRARY SUBJECT REFERENCE | 519.2 An2337 2018 (Browse shelf) | Available | CITU-CL-48829 |
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| 512.9 W516 1994 College algebra with applications / | 515.35 W675 2001 Introduction to differential equation and dynamical system / | 518 C368 2008 Applied numerical methods with MATLAB for engineers and scientist | 519.2 An2337 2018 Introduction to probability / | 519.2 Sci27 2007 Scientists and engineers : guide to probability and statistics / | 519.4 Ep73 2002 An introduction to numerical methods and analysis / | 519.4 Ep73 2002 An introduction to numerical methods and analysis / |
Authors
David F. Anderson, University of Wisconsin, Madison
David F. Anderson is a Professor of Mathematics at the University of Wisconsin, Madison. His research focuses on probability theory and stochastic processes, with applications in the biosciences. He is the author of over thirty research articles and a graduate textbook on the stochastic models utilized in cellular biology. He was awarded the inaugural Institute for Mathematics and its Applications (IMA) Prize in Mathematics in 2014, and was named a Vilas Associate by the University of Wisconsin, Madison in 2016.
Timo Seppäläinen, University of Wisconsin, Madison
Timo Seppäläinen is the John and Abigail Van Vleck Chair of Mathematics at the University of Wisconsin-Madison. He is the author of over seventy research papers in probability theory and a graduate textbook on large deviation theory. He is an elected Fellow of the Institute of Mathematical Statistics. He was an IMS Medallion Lecturer in 2014, an invited speaker at the 2014 International Congress of Mathematicians, and a 2015?16 Simons Fellow.
Benedek Valkó, University of Wisconsin, Madison
Benedek Valkó is a Professor of Mathematics at the University of Wisconsin, Madison. His research focuses on probability theory, in particular in the study of random matrices and interacting stochastic systems. He has published over thirty research papers. He has won a National Science Foundation (NSF) CAREER award and he was a 2017?18 Simons Fellow.
Includes bibliographical references and index.
This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.

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