Colin Aitken, Franco Taroni, Silvia Bozza

Statistics and the Evaluation of Evidence for Forensic Scientists (eBook, PDF)

• Format: PDF

Produktbeschreibung

Statistics and the Evaluation of Evidence for Forensic Scientists The leading resource in the statistical evaluation and interpretation of forensic evidence The third edition of Statistics and the Evaluation of Evidence for Forensic Scientists is fully updated to provide the latest research and developments in the use of statistical techniques to evaluate and interpret evidence. Courts are increasingly aware of the importance of proper evidence assessment when there is an element of uncertainty. Because of the increasing availability of data, the role of statistical and probabilistic reasoning is gaining a higher profile in criminal cases. That's why lawyers, forensic scientists, graduate students, and researchers will find this book an essential resource, one which explores how forensic evidence can be evaluated and interpreted statistically. It's written as an accessible source of information for all those with an interest in the evaluation and interpretation of forensic scientific evidence. * Discusses the entire chain of reasoning-from evidence pre-assessment to court presentation; * Includes material for the understanding of evidence interpretation for single and multiple trace evidence; * Provides real examples and data for improved understanding. Since the first edition of this book was published in 1995, this respected series has remained a leading resource in the statistical evaluation of forensic evidence. It shares knowledge from authors in the fields of statistics and forensic science who are international experts in the area of evidence evaluation and interpretation. This book helps people to deal with uncertainty related to scientific evidence and propositions. It introduces a method of reasoning that shows how to update beliefs coherently and to act rationally. In this edition, readers can find new information on the topics of elicitation, subjective probabilities, decision analysis, and cognitive bias, all discussed in a Bayesian framework.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 1248
• Erscheinungstermin: 24. November 2020
• Englisch
• ISBN-13: 9781119245254
• Artikelnr.: 60674941

Autorenporträt

COLIN G. AITKEN, School of Mathematics, University of Edinburgh, UK FRANCO TARONI, School of Criminal Justice, University of Lausanne, Switzerland SILVIA BOZZA, Department of Economics, Ca' Foscari University of Venice, Italy and School of Criminal Justice, University of Lausanne, Switzerland

Inhaltsangabe

Foreword xvii

Preface to Third Edition xxi

Preface to Second Edition xxx

Preface to First Edition xxxvii

1 Uncertainty in Forensic Science 1

1.1 Introduction 1

1.2 Statistics and the Law 3

1.3 Uncertainty in Scientific Evidence 11

1.3.1 The Frequentist Method 15

1.3.2 Stains of Body Fluids 17

1.3.3 Glass Fragments 21

1.4 Terminology 29

1.5 Types of Data 34

1.6 Populations 36

1.7 Probability 41

1.7.1 Introduction 41

1.7.2 A Standard for Uncertainty 46

1.7.3 Events 55

1.7.4 Classical and Frequentist Definitions of Probability and Their Limitations 57

1.7.5 Subjective Definition of Probability 60

1.7.6 The Quantification of Probability Through a Betting Scheme 64

1.7.7 Probabilities and Frequencies: The Role of Exchangeability 69

1.7.8 Laws of Probability 78

1.7.9 Dependent Events and Background Information 82

1.7.10 Law of Total Probability 91

1.7.11 Updating of Probabilities 96

2 The Evaluation of Evidence 101

2.1 Odds 101

2.1.1 Complementary Events 101

2.1.2 Examples 104

2.1.3 Definition of Odds 105

2.2 Bayes' Theorem 108

2.2.1 Statement of the Theorem 109

2.2.2 Examples 109

2.3 The Odds Form of Bayes' Theorem 121

2.3.1 Likelihood Ratio 121

2.3.2 Bayes' Factor and Likelihood Ratio 125

2.3.3 Three-Way Tables 130

2.3.4 Logarithm of the Likelihood Ratio 134

2.4 The Value of Evidence 138

2.4.1 Evaluation of Forensic Evidence 138

2.4.2 Justification of the Use of the Likelihood Ratio 154

2.4.3 Single Value for the Likelihood Ratio 158

2.4.4 Role of Background Information 161

2.4.5 Summary of Competing Propositions 163

2.4.6 Qualitative Scale for the Value of the Evidence 168

2.5 Errors in Interpretation 180

2.5.1 Fallacy of the Transposed Conditional 186

2.5.2 Source Probability Error 190

2.5.3 Ultimate Issue Error 194

2.5.4 Defence Attorney's Fallacy 194

2.5.5 Probability (Another Match) Error 196

2.5.6 Numerical Conversion Error 199

2.5.7 False Positive Fallacy 202

2.5.8 Expected Value Fallacy 203

2.5.9 Uniqueness 206

2.5.10 Other Difficulties 209

2.5.11 Empirical Evidence of Errors in Interpretation 220

2.6 Misinterpretations 233

2.7 Explanation of Transposed Conditional, Defence Attorney's and False Positive Fallacies 236

2.7.1 Explanation of the Fallacy of the Transposed Conditional 236

2.7.2 Explanation of the Defence Attorney's Fallacy 239

2.7.3 Explanation of the False Positive Fallacy 241

2.8 Making Coherent Decisions 245

2.8.1 Elements of Statistical Decision Theory 246

2.8.2 Decision Analysis: An Example 249

2.9 Graphical Probabilistic Models: Bayesian Networks 254

2.9.1 Elements of the Bayesian Networks 256

2.9.2 The Construction of Bayesian Networks 261

2.9.3 Bayesian Decision Networks (Influence Diagrams) 272

3 Historical Review 279

3.1 Early History 279

3.2 The Dreyfus Case 286

3.3 Statistical Arguments by Early Twentieth-Century Forensic Scientists 293

3.4 People v. Collins 299

3.5 Discriminating Power 307

3.5.1 Derivation 307

3.5.2 Evaluation of Evidence by Discriminating Power 310

3.5.3 Finite Samples 316

3

Rezensionen

"I hope that every forensic laboratory in the United States and Europe has a copy of this book, and that they rapidly wear out from repeated use. It is a tremendous resource. It could also be a valuable textbook for a methods course in criminology departments."

David Banks, Department of Statistical Science, Duke University, Durham, NC, USA