| Record ID | marc_columbia/Columbia-extract-20221130-004.mrc:546759690:1696 |
| Source | marc_columbia |
| Download Link | /show-records/marc_columbia/Columbia-extract-20221130-004.mrc:546759690:1696?format=raw |
LEADER: 01696fam a2200325 a 4500
001 1930974
005 20220609031535.0
008 960524s1996 nyua b 001 0 eng
010 $a 96025714
020 $a0471958034 (cloth)
035 $a(OCoLC)503145419
035 $a(OCoLC)ocn503145419
035 $9AMC7530CU
035 $a(NNC)1930974
035 $a1930974
040 $aDLC$cDLC$dNNC$dOrLoB-B
050 00 $aQA298$b.V67 1996
082 00 $a658.4/.352$220
100 1 $aVose, David.$0http://id.loc.gov/authorities/names/n96052451
245 10 $aQuantitative risk analysis :$ba guide to Monte Carlo simulation modelling /$cDavid Vose.
260 $aNew York ;$aChichester, England :$bWiley,$c1996.
263 $a9610
300 $aix, 328 pages :$billustrations ;$c24 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
504 $aIncludes bibliographical references and index.
505 00 $g1.$tIntroduction --$g2.$tWhat is Quantitative Risk Analysis? --$g3.$tProbability theory and statistics --$g4.$tHow Monte Carlo simulation works --$g5.$tProbability Distributions --$g6.$tBuilding a Risk Analysis Model --$g7.$tDeriving Distributions from Data --$g8.$tDefining Distributions from Expert Opinion --$g9.$tModelling Dependencies --$g10.$tProject Risk Analysis --$g11.$tIncorporating Uncertainty into Time Series Projections --$g12.$tPresenting and Interpreting Risk Analysis Results --$g13.$tProblems for the reader to solve.
650 0 $aMonte Carlo method.$0http://id.loc.gov/authorities/subjects/sh85087032
650 0 $aRisk assessment$xMathematical models.$0http://id.loc.gov/authorities/subjects/sh2010110624
852 00 $boff,bus$hQA298$i.V67 1996