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Benford's law : theory, the general law of relative quantities, and forensic fraud detection applications / Alex Ely Kossovsky
| Benford's law : theory, the general law of relative quantities, and forensic fraud detection applications / Alex Ely Kossovsky |
| Autore | Kossovsky, Alex Ely |
| Descrizione fisica | xxi, 649 p. : ill. ; 24 cm |
| Disciplina | 363.25 |
| Soggetto topico |
Fraud investigation - Statistical methods
Fraud - Statistical methods Distribution (Probability theory) Forensic statistics Forensic sciences - Statistical methods |
| ISBN | 9789814651202 (paperback) |
| Classificazione |
AMS 60-01
AMS 60E05 AMS 11K06 AMS 60F15 LC HV8079.F7K67 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991003364879707536 |
Kossovsky, Alex Ely
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| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Data analysis in forensic science [[electronic resource] ] : a Bayesian decision perspective / / Franco Taroni ... [et al.]
| Data analysis in forensic science [[electronic resource] ] : a Bayesian decision perspective / / Franco Taroni ... [et al.] |
| Pubbl/distr/stampa | Chichester, : John Wiley and Sons, 2010 |
| Descrizione fisica | 1 online resource (389 p.) |
| Disciplina | 363.2501/519542 |
| Altri autori (Persone) | TaroniFranco |
| Collana | Statistics in practice |
| Soggetto topico |
Forensic sciences - Statistical methods
Bayesian statistical decision theory |
| ISBN |
1-282-54840-9
9786612548406 0-470-66508-4 0-470-66507-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Data Analysis in Forensic Science; Contents; Foreword; Preface; I The Foundations of Inference and Decision in Forensic Science; 1 Introduction; 1.1 The Inevitability of Uncertainty; 1.2 Desiderata in Evidential Assessment; 1.3 The Importance of the Propositional Framework and the Nature of Evidential Assessment; 1.4 From Desiderata to Applications; 1.5 The Bayesian Core of Forensic Science; 1.6 Structure of the Book; 2 Scientific Reasoning and Decision Making; 2.1 Coherent Reasoning Under Uncertainty; 2.1.1 A rational betting policy; 2.1.2 A rational policy for combining degrees of belief
2.1.3 A rational policy for changing degrees of belief2.2 Coherent Decision Making Under Uncertainty; 2.2.1 A method for measuring the value of consequences; 2.2.2 The consequences of rational preferences; 2.2.3 Intermezzo: some more thoughts about rational preferences; 2.2.4 The implementation of coherent decision making under uncertainty: Bayesian networks; 2.2.5 The connection between pragmatic and epistemic standards of reasoning; 2.3 Scientific Reasoning as Coherent Decision Making; 2.3.1 Bayes' theorem; 2.3.2 The theories' race; 2.3.3 Statistical reasoning: the models' race 2.3.4 Probabilistic model building: betting on random quantities2.4 Forensic Reasoning as Coherent Decision Making; 2.4.1 Likelihood ratios and the 'weight of evidence'; 2.4.2 The expected value of information; 2.4.3 The hypotheses' race in the law; 3 Concepts of Statistical Science and Decision Theory; 3.1 Random Variables and Distribution Functions; 3.1.1 Univariate random variables; 3.1.2 Measures of location and variability; 3.1.3 Multiple random variables; 3.2 Statistical Inference and Decision Theory; 3.2.1 Utility theory; 3.2.2 Maximizing expected utility; 3.2.3 The loss function 3.3 The Bayesian Paradigm3.3.1 Sequential use of Bayes' theorem; 3.3.2 Principles of rational inference in statistics; 3.3.3 Prior distributions; 3.3.4 Predictive distributions; 3.3.5 Markov Chain Monte Carlo methods (MCMC); 3.4 Bayesian Decision Theory; 3.4.1 Optimal decisions; 3.4.2 Standard loss functions; 3.5 R Code; II Forensic Data Analysis; 4 Point Estimation; 4.1 Introduction; 4.2 Bayesian Decision for a Proportion; 4.2.1 Estimation when there are zero occurrences in a sample; 4.2.2 Prior probabilities; 4.2.3 Prediction 4.2.4 Inference for 0 in the presence of background data on the number of successes4.2.5 Multinomial variables; 4.3 Bayesian Decision for a Poisson Mean; 4.3.1 Inference about the Poisson parameter in the absence of background events; 4.3.2 Inference about the Poisson parameter in the presence of background events; 4.3.3 Forensic inference using graphical models; 4.4 Bayesian Decision for Normal Mean; 4.4.1 Case with known variance; 4.4.2 Case with unknown variance; 4.4.3 Estimation of the mean in the presence of background data; 4.5 R Code; 5 Credible Intervals; 5.1 Introduction 5.2 Credible Intervals and Lower Bounds |
| Record Nr. | UNINA-9910140587703321 |
| Chichester, : John Wiley and Sons, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data analysis in forensic science : a Bayesian decision perspective / / Franco Taroni ... [et al.]
| Data analysis in forensic science : a Bayesian decision perspective / / Franco Taroni ... [et al.] |
| Pubbl/distr/stampa | Chichester, : John Wiley and Sons, 2010 |
| Descrizione fisica | 1 online resource (389 p.) |
| Disciplina | 363.2501/519542 |
| Altri autori (Persone) | TaroniFranco |
| Collana | Statistics in practice |
| Soggetto topico |
Forensic sciences - Statistical methods
Bayesian statistical decision theory |
| ISBN |
1-282-54840-9
9786612548406 0-470-66508-4 0-470-66507-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Data Analysis in Forensic Science; Contents; Foreword; Preface; I The Foundations of Inference and Decision in Forensic Science; 1 Introduction; 1.1 The Inevitability of Uncertainty; 1.2 Desiderata in Evidential Assessment; 1.3 The Importance of the Propositional Framework and the Nature of Evidential Assessment; 1.4 From Desiderata to Applications; 1.5 The Bayesian Core of Forensic Science; 1.6 Structure of the Book; 2 Scientific Reasoning and Decision Making; 2.1 Coherent Reasoning Under Uncertainty; 2.1.1 A rational betting policy; 2.1.2 A rational policy for combining degrees of belief
2.1.3 A rational policy for changing degrees of belief2.2 Coherent Decision Making Under Uncertainty; 2.2.1 A method for measuring the value of consequences; 2.2.2 The consequences of rational preferences; 2.2.3 Intermezzo: some more thoughts about rational preferences; 2.2.4 The implementation of coherent decision making under uncertainty: Bayesian networks; 2.2.5 The connection between pragmatic and epistemic standards of reasoning; 2.3 Scientific Reasoning as Coherent Decision Making; 2.3.1 Bayes' theorem; 2.3.2 The theories' race; 2.3.3 Statistical reasoning: the models' race 2.3.4 Probabilistic model building: betting on random quantities2.4 Forensic Reasoning as Coherent Decision Making; 2.4.1 Likelihood ratios and the 'weight of evidence'; 2.4.2 The expected value of information; 2.4.3 The hypotheses' race in the law; 3 Concepts of Statistical Science and Decision Theory; 3.1 Random Variables and Distribution Functions; 3.1.1 Univariate random variables; 3.1.2 Measures of location and variability; 3.1.3 Multiple random variables; 3.2 Statistical Inference and Decision Theory; 3.2.1 Utility theory; 3.2.2 Maximizing expected utility; 3.2.3 The loss function 3.3 The Bayesian Paradigm3.3.1 Sequential use of Bayes' theorem; 3.3.2 Principles of rational inference in statistics; 3.3.3 Prior distributions; 3.3.4 Predictive distributions; 3.3.5 Markov Chain Monte Carlo methods (MCMC); 3.4 Bayesian Decision Theory; 3.4.1 Optimal decisions; 3.4.2 Standard loss functions; 3.5 R Code; II Forensic Data Analysis; 4 Point Estimation; 4.1 Introduction; 4.2 Bayesian Decision for a Proportion; 4.2.1 Estimation when there are zero occurrences in a sample; 4.2.2 Prior probabilities; 4.2.3 Prediction 4.2.4 Inference for 0 in the presence of background data on the number of successes4.2.5 Multinomial variables; 4.3 Bayesian Decision for a Poisson Mean; 4.3.1 Inference about the Poisson parameter in the absence of background events; 4.3.2 Inference about the Poisson parameter in the presence of background events; 4.3.3 Forensic inference using graphical models; 4.4 Bayesian Decision for Normal Mean; 4.4.1 Case with known variance; 4.4.2 Case with unknown variance; 4.4.3 Estimation of the mean in the presence of background data; 4.5 R Code; 5 Credible Intervals; 5.1 Introduction 5.2 Credible Intervals and Lower Bounds |
| Record Nr. | UNINA-9910814422903321 |
| Chichester, : John Wiley and Sons, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Handbook of forensic statistics / / edited by David L. Banks, Karen Kafadar, David H. Kaye, Maria Tackett
| Handbook of forensic statistics / / edited by David L. Banks, Karen Kafadar, David H. Kaye, Maria Tackett |
| Pubbl/distr/stampa | Boca Raton : , : Chapman & Hall/CRC, , 2021 |
| Descrizione fisica | 1 online resource (571 pages) |
| Disciplina | 363.25015195 |
| Collana | Chapman & Hall/CRC handbooks of modern statistical methods |
| Soggetto topico | Forensic sciences - Statistical methods |
| ISBN |
1-000-09606-8
0-367-52770-7 1-000-09620-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910794481903321 |
| Boca Raton : , : Chapman & Hall/CRC, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Handbook of forensic statistics / / edited by David L. Banks, Karen Kafadar, David H. Kaye, Maria Tackett
| Handbook of forensic statistics / / edited by David L. Banks, Karen Kafadar, David H. Kaye, Maria Tackett |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Boca Raton : , : Chapman & Hall/CRC, , 2021 |
| Descrizione fisica | 1 online resource (571 pages) |
| Disciplina |
363.25015195
519.502436325 |
| Collana | Chapman & Hall/CRC handbooks of modern statistical methods |
| Soggetto topico | Forensic sciences - Statistical methods |
| ISBN |
1-000-09606-8
0-367-52770-7 1-000-09620-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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 -- 2.6.2 Hypothesis Testing with p-Values -- 2.6.3 Hypothesis Testing with Confidence Intervals -- 2.7 Issues in Interpreting the Results of Hypothesis Tests, p-Values, and Confidence Coefficients -- 2.7.1 Transposition -- 2.7.2 Multiple Tests: Proof of the Null Hypothesis and Adjusted p-Values -- 2.7.3 Arbitrary Lines -- 2.7.4 Alternatives and Likelihoods -- 2.8 Resampling Methods -- 2.8.1 Bootstrap Estimates -- 2.8.2 Permutation Tests -- Acknowledgments -- References -- 3. Bayesian Methods and Forensic Inference -- 3.1 Introduction -- 3.2 The Basics -- 3.2.1 A Beta-Binomial Mock Example -- 3.2.2 A Gamma-Poisson Mock Example -- 3.3 Markov Chain Monte Carlo -- 3.4 Broad Applications -- 3.5 Summary -- Acknowledgments -- References -- 4. Comparing Philosophies of Statistical Inference. 4.1 Inferential Philosophies -- 4.1.1 Frequentist Inference -- 4.1.2 Bayesian Inference -- 4.1.3 Other Approaches to Inference -- 4.1.3.1 Fiducial Inference -- 4.1.3.2 Likelihood Inference -- 4.1.3.3 Confidence Distributions -- 4.2 Comparing the Approaches -- 4.2.1 Planning Studies Using Frequentist Inference -- 4.2.2 Challenges for Frequentist Inference -- 4.2.3 Flexible Inference with Bayesian Methods -- 4.2.4 Model Modifications and Adjustments -- 4.2.5 The Prior Distribution and the Definition of Probability -- 4.3 Relevance to Forensic Statistics -- 4.3.1 Likelihood Ratios and Bayes Factors -- 4.3.2 Two-Stage Procedures in Forensic Science -- 4.3.3 Forensic Evidence as Expert Opinion and Error Rates -- 4.4 Summary -- References -- 5. Decision Theory -- 5.1 Introduction -- 5.2 Concepts of Statistical Decision Theory -- 5.2.1 Preliminaries: Basic Elements of Decision Problems -- 5.2.2 Utility Theory -- 5.2.3 Implications of the Expected Utility Maximisation Principle -- 5.2.4 The Loss Function -- 5.2.5 Particular Forms of the Expected Utility Maximisation Principle -- 5.2.6 Likelihood Ratios in the Decision Framework -- 5.3 Decision Theory in the Law and Forensic Science -- 5.3.1 Legal Applications -- 5.3.2 Forensic Science Applications 5.3.2.1 Forensic Identification -- 5.3.2.2 Understanding Probability Assignment as a Decision: The Use of Proper Scoring Rules -- 5.3.2.3 Other Forensic Decision Problems: Consignment Inspection -- 5.4 Discussion and Conclusions -- 5.5 Further Readings -- 5.5.1 Forensic Science -- 5.5.2 General -- Acknowledgments -- References -- 6. Association Does Not Imply Discrimination: Clarifying When Matches Are (and Are Not) Meaningful -- 6.1 Introduction -- 6.2 Association and Discrimination -- 6.2.1 Quality of Test: Sensitivity and Specificity -- 6.2.2 Sources of Error -- 6.2.3 Weight of Evidence: The Likelihood Ratio. 6.2.4 Useful Databases for Ascertaining Discriminatory Power -- 6.2.5 Conflating Conditional Statements: The Prosecutor's Fallacy -- 6.3 Examples: The Discriminatory Power of Forensic Evidence -- 6.3.1 Arson Investigation -- 6.3.2 Other Types of Forensic Evidence: DNA, Fingerprints, and Shoe Prints -- 6.3.3 Abusive Head Trauma -- 6.4 Conclusion -- References -- 7. Validation of Forensic Automatic Likelihood Ratio Methods -- 7.1 Introduction -- 7.1.1 Scope -- 7.1.2 Aim -- 7.1.3 Structure -- 7.2 Validation Process -- 7.2.1 Standardization -- 7.2.2 Validation of Theoretical and Empirical Aspects -- 7.2.3 Performance Characteristics for Automatic LR Methods -- 7.2.4 Empirical Validation -- 7.2.5 Validation Protocol -- 7.3 Primary Performance Characteristics -- 7.3.1 Performance of Probabilities by Proper Scoring Rules -- 7.3.2 Discrimination and Calibration of Probabilities -- 7.3.3 Performance of Likelihood Ratios -- 7.3.4 Properties of Well-Calibrated Likelihood Ratios -- 7.3.5 Examples with Primary Performance Characteristics -- 7.4 Secondary Performance Characteristics -- 7.4.1 Robustness -- 7.4.2 Monotonicity -- 7.4.3 Generalization -- 7.5 Conclusion -- References -- 8. Bayesian Networks in Forensic Science -- 8.1 Introduction -- 8.2 Probability Logic -- 8.3 Simple Bayesian Networks for Forensic Problems -- 8.4 Object-Oriented Bayesian Networks -- 8.5 Forensic Genetics -- 8.5.1 Bayesian Networks for Simple Criminal Identification -- 8.5.2 Simple Disputed Paternity -- 8.5.3 Bayesian Networks for Complex Criminal Cases Involving Family Relationships -- 8.5.4 Mutation -- 8.6 Bayesian Networks for Analysing Mixed DNA Profiles -- 8.6.1 Discrete Features -- 8.6.2 Continuous Features -- 8.7 Analysis of Sensitivity to Assumptions on Founder Genes -- 8.7.1 Uncertainty in Allele Frequencies -- 8.7.2 Heterogeneous Reference Population -- 8.8 Conclusions. Appendix 8A: Bayesian Network Basics -- 8A.1 Qualitative Structure -- 8A.2 Independence Properties -- 8A.3 Quantitative Structure -- 8A.4 Computation -- References -- Section III: Legal and Psychological Dimensions -- 9. How Well Do Lay People Comprehend Statistical Statements from Forensic Scientists? -- 9.1 Methodological Overview -- 9.2 Consistency -- 9.2.1 Framing -- 9.2.2 Format -- 9.3 Sensitivity -- 9.4 (In)Coherence -- 9.4.1 Prosecutor's Fallacy -- 9.4.2 Defense Attorney's Fallacy -- 9.4.3 Directional Errors -- 9.4.4 Aggregation Errors -- 9.5 Ability -- 9.6 Orthodoxy -- 9.7 Discussion -- 9.8 Conclusion -- References -- 10. Forensic Statistics in the Courtroom -- 10.1 The Purpose, Form, and Prerequisites of Expert Testimony -- 10.1.1 Lay and Expert Testimony -- 10.1.2 Qualifications for Statistical Experts (and Experts Who Use Statistics) -- 10.1.3 Forms of Statistical Expert Testimony -- 10.1.4 Reasonable Scientific or Statistical Certainty -- 10.2 Special Rules for Scientific Expert Testimony* -- 10.2.1 The General-Acceptance Standard -- 10.2.2 The Scientific-Validity Standard -- 10.3 Selected Evidentiary Issues in Forensic Statistics -- 10.3.1 Two Uses of Statistical Analysis as Evidence -- 10.3.2 Theory and Application -- 10.3.3 Error Rates in Determining Admissibility -- 10.3.4 Error Rates, Likelihood Ratios, and Bayes Factors for Quantifying Probative Value -- 10.4 Conclusion -- References -- Cases and Rules -- Section IV: Applications of Statistics to Particular Fields in Forensic Science -- 11. DNA Frequencies and Probabilities -- 11.1 Introduction -- 11.2 Likelihood Ratios -- 11.3 Population Genetics -- 11.3.1 Single Loci -- 11.3.2 Multiple Loci -- 11.3.3 Population Structure -- 11.3.4 Lineage Markers -- 11.4 Mixtures -- 11.4.1 Semi-Continuous Model -- 11.4.2 Continuous Model -- 11.5 DNA Sequence Data -- 11.6 Future Directions. 11.7 Conclusions. |
| Record Nr. | UNINA-9910811708003321 |
| Boca Raton : , : Chapman & Hall/CRC, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Introduction to data analysis with R for forensic scientists / / James Michael Curran
| Introduction to data analysis with R for forensic scientists / / James Michael Curran |
| Autore | Curran James Michael |
| Pubbl/distr/stampa | Boca Raton, Fla. : , : CRC Press, , 2011 |
| Descrizione fisica | 1 online resource (324 p.) |
| Disciplina | 363.25/6028552 |
| Collana | International forensic science and investigation series |
| Soggetto topico |
Forensic sciences - Statistical methods
Forensic statistics Forensic sciences - Data processing Criminal investigation - Data processing R (Computer program language) |
| Soggetto genere / forma | Electronic books. |
| ISBN |
0-429-25021-5
1-4200-8827-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front cover; Dedication; About the author; Acknowledgments; Contents; List of Figures; List of Tables; Chapter 1: Introduction; Chapter 2: Basic statistics; Chapter 3: Graphics; Chapter 4: Hypothesis tests and sampling theory; Chapter 5: The linear model; Chapter 6: Modeling count and proportion data; Chapter 7: The design of experiments; Bibliography; Back cover |
| Record Nr. | UNINA-9910459475803321 |
|
Curran James Michael
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| Boca Raton, Fla. : , : CRC Press, , 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Introduction to data analysis with R for forensic scientists / / James Michael Curran
| Introduction to data analysis with R for forensic scientists / / James Michael Curran |
| Autore | Curran James Michael |
| Pubbl/distr/stampa | Boca Raton, Fla. : , : CRC Press, , 2011 |
| Descrizione fisica | 1 online resource (324 p.) |
| Disciplina | 363.25/6028552 |
| Collana | International forensic science and investigation series |
| Soggetto topico |
Forensic sciences - Statistical methods
Forensic statistics Forensic sciences - Data processing Criminal investigation - Data processing R (Computer program language) |
| ISBN |
1-138-38144-6
0-429-25021-5 1-4200-8827-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front cover; Dedication; About the author; Acknowledgments; Contents; List of Figures; List of Tables; Chapter 1: Introduction; Chapter 2: Basic statistics; Chapter 3: Graphics; Chapter 4: Hypothesis tests and sampling theory; Chapter 5: The linear model; Chapter 6: Modeling count and proportion data; Chapter 7: The design of experiments; Bibliography; Back cover |
| Record Nr. | UNINA-9910785134203321 |
|
Curran James Michael
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| Boca Raton, Fla. : , : CRC Press, , 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Introduction to data analysis with R for forensic scientists / / James Michael Curran
| Introduction to data analysis with R for forensic scientists / / James Michael Curran |
| Autore | Curran James Michael |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Boca Raton, FL, : CRC Press, 2010 |
| Descrizione fisica | 1 online resource (324 p.) |
| Disciplina | 363.25/6028552 |
| Collana | International forensic science and investigation series |
| Soggetto topico |
Forensic sciences - Statistical methods
Forensic statistics Forensic sciences - Data processing Criminal investigation - Data processing R (Computer program language) |
| ISBN |
1-138-38144-6
0-429-25021-5 1-4200-8827-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front cover; Dedication; About the author; Acknowledgments; Contents; List of Figures; List of Tables; Chapter 1: Introduction; Chapter 2: Basic statistics; Chapter 3: Graphics; Chapter 4: Hypothesis tests and sampling theory; Chapter 5: The linear model; Chapter 6: Modeling count and proportion data; Chapter 7: The design of experiments; Bibliography; Back cover |
| Record Nr. | UNINA-9910815397903321 |
|
Curran James Michael
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| Boca Raton, FL, : CRC Press, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Measurement uncertainty in forensic science : a practical guide / / by Suzanne Bell
| Measurement uncertainty in forensic science : a practical guide / / by Suzanne Bell |
| Autore | Bell Suzanne <1940, > |
| Pubbl/distr/stampa | Boca Raton, FL : , : CRC Press, an imprint of Taylor and Francis, , [2016] |
| Descrizione fisica | 1 online resource (174 pages) : illustrations, tables |
| Disciplina | 363.25015195 |
| Soggetto topico |
Forensic sciences - Statistical methods
Measurement uncertainty (Statistics) |
| ISBN |
1-315-40090-1
1-315-40089-8 1-315-40088-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- List of Figures -- List of Tables -- Preface -- Author -- 1 Forensic Measurements, Metrology, and Uncertainty -- 1.1 Consequence -- 1.2 The Best Way -- 1.3 Measurement Science and Traceability -- 1.4 Accuracy and Variability -- 1.5 Foundational Skills and Materials -- 1.6 Summary and Preview -- References -- 2 Sources of Uncertainty -- 2.1 Where Does Uncertainty Come From? -- 2.2 Diameter of a Penny -- 2.3 Weighing Pennies -- 2.4 The Need to Know -- 2.5 A Flowchart -- 2.6 The Elephant in the Room -- 2.7 Summary -- Further Reading -- 3 Foundational Concepts -- 3.1 Closeness to the True Value -- 3.2 Replicate Measurements and Spread -- 3.3 The Normal Distribution (and Others) -- 3.4 Figures of Merit -- 3.5 Summary and Preview -- References -- 4 Process and Procedures -- 4.1 Uncertainty Defined -- 4.2 Process of Uncertainty Estimation -- 4.3 Tools for Identifying Contributors: Measurement of�Density -- 4.4 Summary and Preview -- References -- 5 Measurement Assurance: Distances, Crime Scenes, and Firearms -- 5.1 Distance Measurement -- 5.2 Capturing Uncertainty -- 5.3 Firearms Measurements -- 5.4 Summary and Preview -- References -- 6 Uncertainty and�Weighing -- 6.1 How Balances Work -- 6.2 Buoyancy -- 6.3 Uncertainty Associated with the Balance -- 6.4 Balance Calibration -- 6.5 Uncertainty Budget with Balance Parameters -- 6.6 Uncertainty Budget with Parameters from a Calibration Certicfiate -- 6.7 Measurement Assurance and Control Chart Approach -- 6.8 Control Charts -- 6.9 Correlation of Events -- 6.10 Correlation and Weighing -- 6.11 Combined Example -- 6.12 Summary and Preview -- References -- 7 Breath Alcohol -- 7.1 Measuring Breath Alcohol -- 7.2 Dry Gas Calibration -- 7.3 Eeffctive Degrees of Freedom -- 7.4 Wet Gas Calibration -- 7.5 Uncertainty and Simulators -- 7.6 Field Use and Uncertainty -- 7.7 Summary and Preview -- References -- 8 Miscellaneous Topics -- 8.1 Quantitative Analysis -- 8.2 Sampling -- 8.3 Sensitivity Coefficients -- 8.4 Uncertainty and Equations -- 8.5 Accuracy and Uncertainty -- 8.6 Summary -- References -- Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- U -- V -- W. |
| Record Nr. | UNINA-9910155138103321 |
|
Bell Suzanne <1940, >
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| Boca Raton, FL : , : CRC Press, an imprint of Taylor and Francis, , [2016] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistics and the evaluation of evidence for forensic scientists / / Colin G G Aitken, Franco Taroni, Silvia Bozza
| Statistics and the evaluation of evidence for forensic scientists / / Colin G G Aitken, Franco Taroni, Silvia Bozza |
| Autore | Aitken C. G. G. |
| Edizione | [Third edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2020] |
| Descrizione fisica | 1 online resource (1,251 pages) |
| Disciplina | 363.25015195 |
| Soggetto topico | Forensic sciences - Statistical methods |
| ISBN |
9781119245438
1-119-24541-9 1-119-24525-7 1-119-24543-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910555166003321 |
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Aitken C. G. G.
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| Hoboken, New Jersey : , : Wiley, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
