Handbook of Forensic Statistics

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Banks, David L.
Otros Autores: Kafadar, Karen, Kaye, David H., Tackett, Maria
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Milton : CRC Press LLC, 2020.
Colección:Chapman and Hall/CRC Handbooks of Modern Statistical Methods Ser.
Temas:
Forensic sciences > Statistical methods.
Criminalistique > Méthodes statistiques.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover
  • Half Title
  • Series Page
  • Title Page
  • Copyright Page
  • Dedication
  • Contents
  • Foreword
  • Preface
  • Editors
  • Contributors
  • Section I: Perspectives on Forensic Statistics
  • 1. The History of Forensic Inference and Statistics: A Thematic Perspective
  • 1.1 Introduction
  • 1.2 Forensic Science and the Evaluation of Evidence
  • 1.3 The Need for an Interpretative Model
  • 1.4 Support of Judicial Disciplines for a Scientific Presentation of the Value of Evidence
  • 1.5 Probability of Proposition Given Evidence and of Evidence Given Proposition
  • 1.6 Quantification of the Value of Evidence Using Alternative Numerical Summaries
  • 1.7 Change from Two-Stage Approach to Continuous Approach
  • 1.8 Presentation of Evidence: New Challenges to Solve
  • 1.8.1 The Island Problem and Results of a Database Selection
  • 1.8.2 Profile Probability vs Conditional Profile Probability
  • 1.8.3 Evaluation by Taking Errors into Account
  • 1.9 A Minimum Value for the Profile Probability
  • 1.10 Propositions and Pre-Assessment
  • 1.10.1 The Choice of Propositions
  • 1.10.2 The Pre-Assessment
  • 1.11 Translation of a Numerical Value into a Verbal Equivalent
  • 1.12 Assessment of Performance
  • 1.13 Role for Likelihood Ratio as aMeasure for Investigation as Well as for Evaluation
  • 1.14 Probabilistic GraphicalModels
  • 1.14.1 Bayesian Networks
  • 1.14.2 Bayesian Networks to Manage 'Masses' of Evidence
  • 1.14.3 Bayesian Networks in Judicial Contexts
  • 1.14.4 Bayesian Networks in Forensic Science: Particular Case Modeling
  • 1.14.5 Bayesian Networks in Forensic Science: Generic Patterns of Inference
  • 1.15 Not Only Inference: The Way to Make a Decision
  • 1.15.1 The Objectives and Ingredients of Decision Theory
  • 1.15.2 Graphical Models
  • 1.16 The Existence or Otherwise of a True Value of the Evidence
  • Acknowledgments
  • References
  • Section II: General Concepts andMethods
  • 2. Frequentist Methods for Statistical Inference
  • 2.1 Introduction
  • 2.2 Definitions and Notation
  • 2.2.1 Data and Evidence
  • 2.3 Random Variables and Probability Distributions
  • 2.3.1 Sampling from a Distribution or Population
  • 2.4 Estimation
  • 2.4.1 Properties of Point Estimators
  • 2.4.2 Estimating Allele Proportions 2.4.2.1 A Point Estimate
  • 2.4.2.2 Constructing a Confidence Interval
  • 2.4.2.3 Choosing a Confidence Coefficient
  • 2.4.3 Estimating a False Positive Probability Through an Experiment 2.4.3.1 The Design of Experiments to Test Categorical Source
  • 2.4.3.2 An Experiment to Test Categorical Judgments of Latent Print Examiners
  • 2.4.3.3 Constructing Confidence Intervals
  • 2.4.4 Interpreting Confidence Intervals
  • 2.5 p-Values
  • 2.5.1 p-Values in a Comparison of Glass Fragments
  • 2.5.2 Interpreting p-Values
  • 2.6 Hypothesis Tests
  • 2.6.1 Classical Hypothesis Tests for Refractive Index Matching 2.6.1.1 Type I Errors and the Size of a Test
  • 2.6.1.2 Type II Errors and the Power of a Test

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