000 03774nam a22005775i 4500
001 978-0-387-74995-2
003 DE-He213
005 20181204133144.0
007 cr nn 008mamaa
008 100715s2009 xxu| s |||| 0|eng d
020 _a9780387749952
_9978-0-387-74995-2
024 7 _a10.1007/978-0-387-74995-2
_2doi
040 _aISI Library, Kolkata
050 4 _aQA273.A1-274.9
050 4 _aQA274-274.9
072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aPBT
_2thema
072 7 _aPBWL
_2thema
082 0 4 _a519.2
_223
100 1 _aLefebvre, Mario.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aBasic Probability Theory with Applications
_h[electronic resource] /
_cby Mario Lefebvre.
264 1 _aNew York, NY :
_bSpringer New York,
_c2009.
300 _aXVI, 340 p. 50 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Undergraduate Texts in Mathematics and Technology,
_x1867-5506
505 0 _aPreface -- Review of Differential Calculus -- Elementary Probability -- Random Variables -- Random Vectors -- Reliability -- Queueing -- Time Series -- Appendix A: List of Symbols and Abbreviations -- Appendix B: Statistical Tables -- Appendix C: Solutions to 'Solved Exercises' -- Appendix D: Answers to Even-Numbered Exercises -- Appendix E: Answers to Multiple-Choice Questions -- References -- Index.
520 _aThis book presents elementary probability theory with interesting and well-chosen applications that illustrate the theory. An introductory chapter reviews the basic elements of differential calculus which are used in the material to follow. The theory is presented systematically, beginning with the main results in elementary probability theory. This is followed by material on random variables. Random vectors, including the all important central limit theorem, are treated next. The last three chapters concentrate on applications of this theory in the areas of reliability theory, basic queuing models, and time series. Examples are elegantly woven into the text and over 400 exercises reinforce the material and provide students with ample practice. This textbook can be used by undergraduate students in pure and applied sciences such as mathematics, engineering, computer science, finance and economics. A separate solutions manual is available to instructors who adopt the text for their course.
650 0 _aDistribution (Probability theory.
650 0 _aEngineering mathematics.
650 0 _aComputer science.
650 0 _aEconomic theory.
650 1 4 _aProbability Theory and Stochastic Processes.
_0http://scigraph.springernature.com/things/product-market-codes/M27004
650 2 4 _aMathematical and Computational Engineering.
_0http://scigraph.springernature.com/things/product-market-codes/T11006
650 2 4 _aProbability and Statistics in Computer Science.
_0http://scigraph.springernature.com/things/product-market-codes/I17036
650 2 4 _aEconomic Theory/Quantitative Economics/Mathematical Methods.
_0http://scigraph.springernature.com/things/product-market-codes/W29000
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387567075
776 0 8 _iPrinted edition:
_z9780387749945
776 0 8 _iPrinted edition:
_z9781461429234
776 0 8 _iPrinted edition:
_z9781493976126
830 0 _aSpringer Undergraduate Texts in Mathematics and Technology,
_x1867-5506
856 4 0 _uhttps://doi.org/10.1007/978-0-387-74995-2
912 _aZDB-2-SMA
942 _cEB
950 _aMathematics and Statistics (Springer-11649)
999 _c426119
_d426119