MARC Record from marc_openlibraries_sanfranciscopubliclibrary

LEADER: 03332cam a2200505 a 4500
001 779264864
003 OCoLC
005 20151005102528.0
008 120402s2012 nyua b 001 0 eng
010 $a2012010536
016 7 $a016057795$2Uk
020 $a9781107658561
020 $a110765856X
035 $a779264864
040 $aDLC$beng$cDLC$dYDX$dBTCTA$dCDX$dOCLCO$dYDXCP$dYNK$dUKMGB$dBWX$dIAD$dIUL$dSFR$dUtOrBLW
042 $apcc
049 $aSFRA
050 00 $aQA273$b.T48 2012
082 00 $a519.2$223
092 $a519.2$bT449u 2012
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
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
338 $avolume$bnc$2rdacarrier
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"--Provided 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.
907 $a.b25631160$b12-20-18$c10-05-12
998 $axbt$b11-02-12$cm$da $e-$feng$gnyu$h0$i0
957 00 $aOCLC reclamation of 2017-18
907 $a.b25631160$b10-01-15$c10-05-12
938 $aBaker and Taylor$bBTCP$nBK0010853801
956 $aPre-reclamation 001 value: ocn779264864
980 $a1012 KL
998 $axbt$b11-02-12$cm$da$e-$feng$gnyu$h0$i0
994 $aC0$bSFR
999 $yMARS
945 $a519.2$bT449u 2012$d07-18-2017 17:04$e05-05-2017 13:04$f0$g0$h05-24-17$i31223101731991$j101$0323$k08-08-17$lxbtci$o-$p$48.00$q-$r-$sn $t1$u24$v30$w0$x1$y.i71699703$z12-18-12