Statistics and the Evaluation of Evidence for Forensic Scientists. Franco Taroni

      1  Cover

      2  Wiley Series in Statistics in Practice

      3  Statistics and the Evaluation of Evidence for Forensic Scientists

      4  Copyright

      5  Dedication

      6  Foreword

      7  Preface to Third Edition

      8  Preface to Second Edition Note

      9  1 Uncertainty in Forensic Science 1.1 Introduction 1.2 Statistics and the Law 1.3 Uncertainty in Scientific Evidence 1.4 Terminology 1.5 Types of Data 1.6 Populations 1.7 Probability Notes

      10  2 The Evaluation of Evidence 2.1 Odds 2.2 Bayes' Theorem 2.3 The Odds Form of Bayes' Theorem 2.4 The Value of Evidence 2.5 Errors in Interpretation 2.6 Misinterpretations 2.7 Explanation of Transposed Conditional, Defence Attorney's and False Positive Fallacies 2.8 Making Coherent Decisions 2.9 Graphical Probabilistic Models: Bayesian Networks Notes

      11  3 Historical Review 3.1 Early History 3.2 The Dreyfus Case 3.3 Statistical Arguments by Early Twentieth‐Century Forensic Scientists 3.4 People v. Collins 3.5 Discriminating Power 3.6 Significance Probabilities 3.7 Coincidence Probabilities 3.8 Likelihood Ratio Notes

      12  4 Bayesian Inference 4.1 Introduction 4.2 Inference for a Proportion 4.3 Sampling 4.4 Bayesian Networks for Sampling Inspection 4.5 Inference for a Normal Mean 4.6 Quantity Estimation 4.7 Decision Analysis Notes

      13  5 Evidence and Propositions: Theory 5.1 The Choice of Propositions and Pre‐Assessment 5.2 Levels of Propositions and Roles of the Forensic Scientist 5.3 The Formal Development of a Likelihood Ratio for Different Propositions and Discrete Characteristics 5.4 Validation of Bayesian Network Structures: An Example 5.5 Pre‐Assessment 5.6 Combination of Items of Evidence Notes

      14  6 Evidence and Propositions: Practice 6.1 Examples for Evaluation given Source Level Propositions 6.2 Examples for Evaluation given Activity Level Propositions 6.3 Examples for Evaluation given Offence Level Propositions 6.4 Summary Notes

      15  7 Data Analysis 7.1 Introduction 7.2 Theory for Discrete Data 7.3 Theory for Continuous Univariate Data 7.4 Normal Between‐Source Variation 7.5 Non‐normal Between‐Source Variation 7.6 Multivariate Analysis 7.7 Discrimination 7.8