000 04457nam a22004935i 4500
001 978-0-8176-8409-9
003 DE-He213
005 20140220082454.0
007 cr nn 008mamaa
008 131113s2014 xxu| s |||| 0|eng d
020 _a9780817684099
_9978-0-8176-8409-9
024 7 _a10.1007/978-0-8176-8409-9
_2doi
050 4 _aQA273.A1-274.9
050 4 _aQA274-274.9
072 7 _aPBT
_2bicssc
072 7 _aPBWL
_2bicssc
072 7 _aMAT029000
_2bisacsh
082 0 4 _a519.2
_223
100 1 _aResnick, Sidney I.
_eauthor.
245 1 2 _aA Probability Path
_h[electronic resource] /
_cby Sidney I. Resnick.
264 1 _aBoston, MA :
_bBirkhäuser Boston :
_bImprint: Birkhäuser,
_c2014.
300 _aXIV, 453 p. 11 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aModern Birkhäuser Classics,
_x2197-1803
520 _aMany probability books are written by mathematicians and have the built-in bias that the reader is assumed to be a mathematician coming to the material for its beauty. This textbook is geared towards beginning graduate students from a variety of disciplines whose primary focus is not necessarily mathematics for its own sake. Instead, A Probability Path is designed for those requiring a deep understanding of advanced probability for their research in statistics, applied probability, biology, operations research, mathematical finance, and engineering.   A one-semester course is laid out in an efficient and readable manner covering the core material. The first three chapters provide a functioning knowledge of measure theory. Chapter 4 discusses independence, with expectation and integration covered in Chapter 5, followed by topics on different modes of convergence, laws of large numbers with applications to statistics (quantile and distribution function estimation), and applied probability. Two subsequent chapters offer a careful treatment of convergence in distribution and the central limit theorem. The final chapter treats conditional expectation and martingales, closing with a discussion of two fundamental theorems of mathematical finance.   Like Adventures in Stochastic Processes, Resnick’s related and very successful textbook, A Probability Path is rich in appropriate examples, illustrations, and problems, and is suitable for classroom use or self-study. The present uncorrected, softcover reprint is designed to make this classic textbook available to a wider audience.                                                             This book is different from the classical textbooks on probability theory in that it treats the measure theoretic background not as a prerequisite but as an integral part of probability theory. The result is that the reader gets a thorough and well-structured framework needed to understand the deeper concepts of current day advanced probability as it is used in statistics, engineering, biology and finance.... The pace of the book is quick and disciplined. Yet there are ample examples sprinkled over the entire book and each chapter finishes with a wealthy section of inspiring problems. —Publications of the International Statistical Institute       This textbook offers material for a one-semester course in probability, addressed to students whose primary focus is not necessarily mathematics.... Each chapter is completed by an exercises section. Carefully selected examples enlighten the reader in many situations. The book is an excellent introduction to probability and its applications. —Revue Roumaine de Mathématiques Pures et Appliquées
650 0 _aMathematics.
650 0 _aDistribution (Probability theory).
650 0 _aMathematical statistics.
650 1 4 _aMathematics.
650 2 4 _aProbability Theory and Stochastic Processes.
650 2 4 _aApplications of Mathematics.
650 2 4 _aOperations Research, Management Science.
650 2 4 _aStatistical Theory and Methods.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780817684082
830 0 _aModern Birkhäuser Classics,
_x2197-1803
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-8176-8409-9
912 _aZDB-2-SMA
999 _c91800
_d91800