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LEADER 00000cam a2200889Ii 4500
001 900640926
003 OCoLC
005 20240129213017.0
006 m o d
007 cr unu||||||||
008 150123s2013 flua ob 000 0 eng d
019 908078355|a958448970|a960996151|a965422878|a967108352
020 9781439809112|q(electronic bk.)
020 1439809119|q(electronic bk.)
020 9780367803018|q(electronic bk.)
020 0367803011|q(electronic bk.)
029 1 CHNEW|b000899345
029 1 DEBBG|bBV042490861
029 1 DEBSZ|b434840394
029 1 GBVCP|b882740628
035 (OCoLC)900640926|z(OCoLC)908078355|z(OCoLC)958448970
|z(OCoLC)960996151|z(OCoLC)965422878|z(OCoLC)967108352
037 CL0500000536|bSafari Books Online
037 9780367803018|bTaylor & Francis
040 UMI|beng|erda|epn|cUMI|dOCLCF|dDEBBG|dEBLCP|dDEBSZ|dN$T
|dORE|dYDX|dLIP|dOCLCO|dOCLCQ|dCEF|dOCLCQ|dAU@|dOCLCQ
|dOCLCA|dOCLCQ|dTYFRS|dOCLCQ|dOCLCA|dOCLCO|dOCLCQ|dOCLCO
049 INap
082 04 658.40301519542
082 04 658.40301519542
099 eBook O'Reilly for Public Libraries
100 1 Fenton, Norman E.,|d1956-|eauthor.
245 10 Risk assessment and decision analysis with Bayesian
networks /|cNorman Fenton, Martin Neil.|h[O'Reilly
electronic resource]
264 1 Boca Raton, FL :|bCRC Press,|c[2013]
264 4 |c©2013
300 1 online resource (xix, 493 pages) :|billustrations
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
500 "A Chapman & Hall book."
504 Includes bibliographical references.
505 0 Chapter 1. There Is More to Assessing Risk Than Statistics
-- Chapter 2. The Need for Causal, Explanatory Models in
Risk Assessment -- Chapter 3. Measuring Uncertainty: The
Inevitability of Subjectivity -- Chapter 4. The Basics of
Probability -- Chapter 5. Bayes' Theorem and Conditional
Probability -- Chapter 6. From Bayes' Theorem to Bayesian
Networks -- Chapter 7. Defining the Structure of Bayesian
Networks -- Chapter 8. Building and Eliciting Node
Probability Tables -- Chapter 9. Numeric Variables and
Continuous Distribution Functions -- Chapter 10.
Hypothesis Testing and Confidence Intervals -- Chapter 11.
Modeling Operational Risk -- Chapter 12. Systems
Reliability Modeling -- Chapter 13. Bayes and the Law.
520 8 There Is More to Assessing Risk Than
StatisticsIntroductionPredicting Economic Growth: The
Normal Distribution and Its LimitationsPatterns and
Randomness: From School League Tables to Siegfried and
RoyDubious Relationships: Why You Should Be Very Wary of
Correlations andTheir Significance ValuesSpurious
Correlations: How You Can Always Find a Silly 'Cause' of
ExamSuccessThe Danger of Regression: Looking Back When You
Need to Look ForwardThe Danger of AveragesWhen Simpson's
Paradox Becomes More WorrisomeUncertain Information and
Incomplete Information: Do Not Assume They AreDifferentDo
Not Trust Anybody (Even Experts) to Properly Reason about
ProbabilitiesChapter SummaryFurther ReadingThe Need for
Causal, Explanatory Models in Risk
AssessmentIntroductionAre You More Likely to Die in an
Automobile Crash When the Weather IsGood Compared to
Bad?The Limitations of Common Approaches to Risk
AssessmentThinking about Risk Using Causal
AnalysisApplying the Causal Framework to
ArmageddonSummaryFurther ReadingMeasuring Uncertainty: The
Inevitability of SubjectivityIntroductionExperiments,
Outcomes, and EventsFrequentist versus Subjective View of
UncertaintySummaryFurther ReadingThe Basics of
ProbabilityIntroductionSome Observations Leading to Axioms
and Theorems of ProbabilityProbability
DistributionsIndependent Events and Conditional
ProbabilityBinomial DistributionUsing Simple Probability
Theory to Solve Earlier Problems and ExplainWidespread
MisunderstandingsSummaryFurther ReadingBayes' Theorem and
Conditional ProbabilityIntroductionAll Probabilities Are
ConditionalBayes' Theorem Using Bayes' Theorem to Debunk
Some Probability FallaciesSecond-Order
ProbabilitySummaryFurther ReadingFrom Bayes' Theorem to
Bayesian NetworksIntroductionA Very Simple Risk Assessment
ProblemAccounting for Multiple Causes (and Effects)Using
Propagation to Make Special Types of.
520 8 Reasoning PossibleThe Crucial Independence
AssumptionsStructural Properties of BNsPropagation in
Bayesian NetworksUsing BNs to Explain Apparent
ParadoxesSteps in Building and Running a BN
ModelSummaryFurther ReadingTheoretical UnderpinningsBN
ApplicationsNature and Theory of CausalityUncertain
Evidence (Soft and Virtual)Defining the Structure of
Bayesian NetworksIntroductionCausal Inference and Choosing
the Correct Edge DirectionThe IdiomsThe Problems of
Asymmetry and How to Tackle ThemMultiobject Bayesian
Network ModelsThe Missing Variable
FallacyConclusionsFurther ReadingBuilding and Eliciting
Node Probability TablesIntroductionFactorial Growth in the
Size of Probability TablesLabeled Nodes and Comparative
ExpressionsBoolean Nodes and FunctionsRanked
NodesElicitationSummaryFurther ReadingNumeric Variables
and Continuous Distribution FunctionsIntroductionSome
Theory on Functions and Continuous DistributionsStatic
DiscretizationDynamic DiscretizationUsing Dynamic
DiscretizationAvoiding Common Problems When Using Numeric
NodesSummaryFurther ReadingHypothesis Testing and
Confidence IntervalsIntroductionHypothesis
TestingConfidence IntervalsSummaryFurther ReadingModeling
Operational RiskIntroductionThe Swiss Cheese Model for
Rare Catastrophic EventsBow Ties and HazardsFault Tree
Analysis (FTA)Event Tree Analysis (ETA)Soft Systems,
Causal Models, and Risk ArgumentsKUUUB FactorsOperational
Risk in FinanceSummaryFurther ReadingSystems Reliability
ModelingIntroductionProbability of Failure on Demand for
Discrete Use SystemsTime to Failure for Continuous Use
SystemsSystem Failure Diagnosis and Dynamic Bayesian
NetworksDynamic Fault Trees (DFTs)Software Defect
PredictionSummaryFurther ReadingBayes and the
LawIntroductionThe Case for Bayesian Reasoning about Legal
EvidenceBuilding Legal Arguments Using IdiomsThe Evidence
IdiomThe Evidence Accuracy.
520 8 IdiomIdioms to Deal with the Key Notions of "Motive" and
"Opportunity"Idiom for Modeling Dependency between
Different Pieces of EvidenceAlibi Evidence IdiomPutting it
All Together: Vole ExampleUsing BNs to Expose Further
Fallacies of Legal ReasoningSummaryFurther ReadingAppendix
A: The Basics of CountingAppendix B: The Algebra of Node
Probability TablesAppendix C: Junction Tree
AlgorithmAppendix D: Dynamic DiscretizationAppendix E:
Statistical Distributions.
588 0 Print version record.
590 O'Reilly|bO'Reilly Online Learning: Academic/Public
Library Edition
650 0 Bayesian statistical decision theory.
650 0 Decision making.
650 0 Risk management.
650 6 Théorie de la décision bayésienne.
650 6 Prise de décision.
650 6 Gestion du risque.
650 7 decision making.|2aat
650 7 risk management.|2aat
650 7 Bayesian statistical decision theory|2fast
650 7 Decision making|2fast
650 7 Risk management|2fast
650 7 Bayes-Entscheidungstheorie|2gnd
650 7 Bayes-Netz|2gnd
650 7 Entscheidungstheorie|2gnd
650 7 Risikoanalyse|2gnd
700 1 Neil, Martin|q(Martin D.),|eauthor.
776 08 |iPrint version:|aFenton, Norman E., 1956-|tRisk
assessment and decision analysis with Bayesian networks.
|dBoca Raton : Taylor & Francis, ©2013|z9781439809105
|w(DLC) 2012015766|w(OCoLC)855192346
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
learning.oreilly.com/library/view/~/9781439809112/?ar
|zAvailable on O'Reilly for Public Libraries
938 ProQuest Ebook Central|bEBLB|nEBL1543313
938 EBSCOhost|bEBSC|n1499617
938 YBP Library Services|bYANK|n7284187
994 92|bJFN