MARC Record from marc_columbia

LEADER: 02843cam a2200373 a 4500
001 10215289
005 20190731135705.0
008 120402s2012 nyua b 001 0 eng
010 $a 2012010536
035 $a(OCoLC)ocn779264864
040 $aDLC$beng$cDLC$dYDX$dBTCTA$dCDX$dOCLCO$dYDXCP$dYNK$dUKMGB$dBWX$dIAD$dIUL
016 7 $a016057795$2Uk
020 $a9781107658561 (pbk.)
020 $a110765856X (pbk.)
042 $apcc
050 00 $aQA273$b.T48 2012
082 00 $a519.2$223
084 $aMAT029000$2bisacsh
049 $aZCUA
100 1 $aTijms, H. C.
245 10 $aUnderstanding probability /$cHenk Tijms.
250 $a3rd ed.
260 $aNew York :$bCambridge University Press,$c2012.
300 $ax, 562 p. :$bill. ;$c23 cm.
520 $a"Understanding Probability is a unique and stimulating approach to a first course in probability. The first part of the book demystifies probability and uses many wonderful probability applications from everyday life to help the reader develop a feel for probabilities. The second part, covering a wide range of topics, teaches clearly and simply the basics of probability. This fully revised third edition has been packed with even more exercises and examples, and it includes new sections on Bayesian inference, Markov chain Monte Carlo simulation, hitting probabilities in random walks and Brownian motion, and a new chapter on continuous-time Markov chains with applications. Here you will find all the material taught in an introductory probability course. The first part of the book, with its easy-going style, can be read by anybody with a reasonable background in high school mathematics. The second part of the book requires a basic course in calculus"--$cProvided by publisher.
504 $aIncludes bibliographical references (p. 556-557) and index.
505 0 $aPart I. Probability in Action: 1. Probability questions; 2. Law of large numbers and simulation; 3. Probabilities in everyday life; 4. Rare events and lotteries; 5. Probability and statistics; 6. Chance trees and Bayes' rule -- Part II. Essentials of Probability: 7. Foundations of probability theory; 8. Conditional probability and Bayes; 9. Basic rules for discrete random variables; 10. Continuous random variables; 11. Jointly distributed random variables; 12. Multivariate normal distribution; 13. Conditioning by random variables; 14. Generating functions; 15. Discrete-time Markov chains; 16. Continuous-time Markov chains -- Appendix; Counting methods and ex.
650 0 $aProbabilities.
650 0 $aMathematical analysis.
650 0 $aChance.
650 7 $aMATHEMATICS / Probability & Statistics / General$2bisacsh
856 42 $3Cover image$uhttp://assets.cambridge.org/97811076/58561/cover/9781107658561.jpg
852 00 $bbus$hQA273$i.T48 2012
852 00 $boff,bus$hQA273$i.T48 2012