000 04118nam a22004575i 4500
001 978-1-4419-5780-1
003 DE-He213
005 20140220084508.0
007 cr nn 008mamaa
008 100427s2010 xxu| s |||| 0|eng d
020 _a9781441957801
_9978-1-4419-5780-1
024 7 _a10.1007/978-1-4419-5780-1
_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 _aDasGupta, Anirban.
_eauthor.
245 1 0 _aFundamentals of Probability: A First Course
_h[electronic resource] /
_cby Anirban DasGupta.
264 1 _aNew York, NY :
_bSpringer New York,
_c2010.
300 _aXVI, 494p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Texts in Statistics,
_x1431-875X
505 0 _aIntroducing Probability -- The Birthday and Matching Problems -- Conditional Probability and Independence -- Integer-Valued and Discrete Random Variables -- Generating Functions -- Standard Discrete Distributions -- Continuous Random Variables -- Some Special Continuous Distributions -- Normal Distribution -- Normal Approximations and the Central Limit Theorem -- Multivariate Discrete Distributions -- Multidimensional Densities -- Convolutions and Transformations -- Markov Chains and Applications -- Urn Models in Physics and Genetics.
520 _aThis is a text encompassing all of the standard topics in introductory probability theory, together with a significant amount of optional material of emerging importance. The emphasis is on a lucid and accessible writing style, mixed with a large number of interesting examples of a diverse nature. The text will prepare students extremely well for courses in more advanced probability and in statistical theory and for the actuary exam. The book covers combinatorial probability, all the standard univariate discrete and continuous distributions, joint and conditional distributions in the bivariate and the multivariate case, the bivariate normal distribution, moment generating functions, various probability inequalities, the central limit theorem and the laws of large numbers, and the distribution theory of order statistics. In addition, the book gives a complete and accessible treatment of finite Markov chains, and a treatment of modern urn models and statistical genetics. It includes 303 worked out examples and 810 exercises, including a large compendium of supplementary exercises for exam preparation and additional homework. Each chapter has a detailed chapter summary. The appendix includes the important formulas for the distributions in common use and important formulas from calculus, algebra, trigonometry, and geometry. Anirban DasGupta is Professor of Statistics at Purdue University, USA. He has been the main editor of the Lecture Notes and Monographs series, as well as the Collections series of the Institute of Mathematical Statistics, and is currently the Co-editor of the Selected Works in Statistics and Probability series, published by Springer. He has been an associate editor of the Annals of Statistics, Journal of the American Statistical Association, Journal of Statistical Planning and Inference, International Statistical Review, Sankhya, and Metrika. He is the author of Asymptotic Theory of Statistics and Probability, 2008, and of 70 refereed articles on probability and statistics. He is a Fellow of the Institute of Mathematical Statistics.
650 0 _aMathematics.
650 0 _aDistribution (Probability theory).
650 1 4 _aMathematics.
650 2 4 _aProbability Theory and Stochastic Processes.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781441957795
830 0 _aSpringer Texts in Statistics,
_x1431-875X
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4419-5780-1
912 _aZDB-2-SMA
999 _c110524
_d110524