Forensic interpretation of glass evidence

Intended for forensic scientists and students of the discipline, Forensic Interpretation of Glass Evidence provides the practicing forensic scientist with the necessary statistical tools and methodology to introduce forensic glass evidence into the laboratory. With free software available for downloading at the author's Web site, scientists can apply their own data and draw conclusions using principles practiced in the text.
This book contains an introductory chapter on glass evidence procedures and analysis before covering topics such as classical approaches to handling glass evidence, the application of Bayesian statistics to forensic science, and the use of histograms.
By presenting both the physical and chemical examinations performed on glass along with a recommended interpretation, the author allows readers the luxury of having all reference materials contained within a single book. Useful for case-working forensic scientists, this book is ideal for students of forensic science at both the undergraduate and graduate levels, as well anyone currently working in the field.

Author Notes

James M. Curran, Ph.D., is a statistics lecturer at the University of Waikato, Hamilton, New Zealand
Tacha Hicks, Ph.D., graduated with honors in forensic science from the Institute de Police Scientifique et de Criminologie (IPSC) at the University of Lausanne. Since 1996 Dr. Hicks has been involved in both the European Glass Group (EGG) and the Scientific Working Group on Materials (SWGMAT)
John S. Buckleton, Ph.D., is a forensic scientist working in New Zealand

Chapter 1 Examination of Glass	p. 1
1.1 History	p. 1
1.2 Flat Glass	p. 2
1.3 Float Glass	p. 3
1.4 Toughened Glass	p. 3
1.5 Laminated Glass	p. 5
1.6 Glass Composition	p. 5
1.7 Glass Breakage Under Impact	p. 6
1.7.1 Breakage in Flexion	p. 7
1.7.2 Determination of Side of Impact	p. 7
1.7.3 Percussion Cone Breakage	p. 9
1.7.4 Transfer of Glass	p. 10
1.8 Physical Examinations	p. 10
1.9 Examinations of Large Fragments	p. 10
1.9.1 The Comparison of Thickness	p. 10
1.9.2 The Comparison of Color	p. 11
1.9.3 Matching Edges and Matching Hackle Marks	p. 12
1.9.4 Density Comparisons	p. 12
1.10 Examinations Performed on Small and Large Fragments	p. 14
1.10.1 Recovering Glass	p. 14
1.10.2 Examination of Transparent Material to Determine Whether It Is Glass	p. 15
1.10.3 The Examination of Surface Fragments	p. 15
1.10.4 Refractive Index Determinations	p. 17
1.10.5 Dispersion	p. 20
1.10.6 Refractive Index Anomalies	p. 20
1.10.7 The Examination of Tempered (Toughened) Glass by Annealing	p. 21
1.11 Elemental Composition	p. 22
1.11.1 X-Ray Methods	p. 23
1.11.1.1 Classification of Glass Using X-Ray Methods	p. 23
1.11.1.2 Discrimination of Glass Using X-Ray Methods	p. 24
1.11.2 ICP Techniques	p. 24
1.11.2.1 Classification of Glass Using ICP Techniques	p. 24
1.11.2.2 Discrimination of Glass Using ICP Techniques	p. 24
1.12 Summary	p. 26
1.13 Appendix A Snell's Law	p. 26
Chapter 2 The Conventional Approach to Evidence Interpretation	p. 27
2.1 Data Comparison	p. 28
2.1.1 Range Tests and Use of Confidence Intervals	p. 28
2.1.2 Confidence Interval	p. 29
2.2 Statistical Tests and Grouping	p. 31
2.2.1 Grouping	p. 31
2.2.1.1 Agglomerative Methods	p. 31
2.2.1.2 Divisive Methods	p. 32
2.2.1.3 Performance	p. 34
2.2.2 Statistical Tests	p. 35
2.2.2.1 Hypothesis Testing	p. 35
2.2.2.1.1 Student's t-Test	p. 38
2.2.2.1.2 Welch's Modification to the Student's t-Test	p. 39
2.2.2.2 How Many Control Fragments?	p. 43
2.2.2.3 Setting Significance Levels	p. 44
2.2.2.4 Elemental Composition Measurements--Hotelling's T[superscript 2]	p. 45
2.2.2.4.1 The Multiple Comparison Problem	p. 45
2.2.2.4.2 Hotelling's T[superscript 2]--A Method for Comparing Two Multivariate Mean Vectors	p. 46
2.2.2.4.3 Examples	p. 46
2.2.2.4.4 Discussion on the Use of Hotelling's T[superscript 2]	p. 47
2.3 Coincidence Probabilities	p. 47
2.4 Summary	p. 49
2.5 Appendix A	p. 50
2.6 Appendix B	p. 52
2.7 Appendix C	p. 53
Chapter 3 The Bayesian Approach to Evidence Interpretation	p. 55
3.1 Probability--Some Definitions	p. 56
3.2 The Laws of Probability	p. 58
3.2.1 The First Law of Probability	p. 58
3.2.2 The Second Law of Probability	p. 58
3.2.3 The Third Law of Probability	p. 59
3.2.4 The Law of Total Probability	p. 59
3.2.5 Bayes Theorem	p. 60
3.2.6 The Relationship Between Probability and Odds	p. 60
3.2.7 The Odds Form of Bayes Theorem	p. 61
3.3 Bayesian Thinking in Forensic Glass Analysis	p. 63
3.3.1 A Generalized Bayesian Formula	p. 73
3.4 Taking Account of Further Analyses	p. 73
3.5 Search Strategy	p. 74
3.6 Comparison of Measurements: The Continuous Approach	p. 76
3.6.1 A Continuous LR Approach to the Interpretation of Elemental Composition Measurements from Forensic Glass Evidence	p. 81
3.6.1.1 The Continuous Likelihood Ratio for Elemental Observations	p. 81
3.6.1.2 Examples	p. 84
3.6.1.3 Discussion	p. 84
3.7 Summary	p. 84
3.8 Appendix A	p. 85
Chapter 4 Glass Found at Random and Frequency of Glass	p. 87
4.1 Relevant Questions	p. 87
4.2 Availability	p. 88
4.3 Glass Found at Random (Clothing Surveys)	p. 88
4.3.1 Glass Found on the General Population	p. 88
4.3.1.1 Glass Recovered on Garments	p. 88
4.3.1.2 Glass Recovered on Shoes	p. 90
4.3.1.3 Glass Recovered in Hair	p. 91
4.3.2 Glass Recovered on the Suspect Population	p. 91
4.3.2.1 General Trends	p. 91
4.3.2.2 Glass Recovered on Shoes	p. 92
4.4 Comparison Between Suspect and General Populations: An Example	p. 93
4.5 Estimation of the Probability of Finding at Random i Groups of j Fragments	p. 94
4.6 Frequency of the Analyzed Characteristics	p. 96
4.7 Control Glass Data Collections	p. 97
4.8 Clothing Surveys	p. 98
4.9 Characteristics of Glass Found on the General Population	p. 98
4.9.1 Glass Recovered on Garments	p. 98
4.9.2 Glass Recovered on Shoes	p. 99
4.10 Characteristics of Glass Found on the Suspect Population	p. 100
4.11 Comparison Between Suspect and General Populations: An Example	p. 100
4.12 Summary	p. 101
Chapter 5 Transfer and Persistence Studies	p. 103
5.1 Transfer of Glass	p. 103
5.1.1 Transfer of Glass to the Ground	p. 104
5.1.1.1 Number, Size, and Distribution of the Fragments	p. 104
5.1.1.2 Influence of the Window Type and Size	p. 105
5.1.1.3 Presence of an Original Surface	p. 106
5.1.2 Transfer of Glass Broken with a Firearm	p. 107
5.1.3 Transfer of Vehicle Glass	p. 107
5.1.4 Transfer of Glass to Individuals Standing Nearby	p. 107
5.1.5 Transfer of Window Glass to Garments	p. 107
5.1.6 Transfer of Glass with a Pendulum	p. 108
5.1.7 Glass Broken Under Conditions Similar to Casework	p. 108
5.1.8 Transfer of Vehicle Glass and Absence of Glass	p. 111
5.1.9 Transfer of Glass When a Person Enters Through a Window	p. 111
5.1.10 Influence of the Weather on Transfer	p. 111
5.1.11 Transfer of Broken Glass	p. 112
5.1.12 Transfer of Window Glass to Hair	p. 112
5.1.13 Transfer of Window Glass to Footwear	p. 113
5.1.14 Secondary and Tertiary Transfer	p. 113
5.1.15 Transfer: What Do We Know?	p. 114
5.2 Persistence of Glass on Garments	p. 115
5.2.1 Early Studies	p. 116
5.2.2 Persistence of Glass on Clothing	p. 116
5.2.3 Persistence of Glass on Shoes	p. 118
5.2.4 Persistence of Glass in Hair	p. 120
5.3 Main Results of the Studies	p. 120
5.4 Modeling Glass Transfer and Making Estimates	p. 122
5.4.1 Graphical Models	p. 122
5.4.2 A Graphical Model for Assessing Transfer Probabilities	p. 123
5.4.3 Results	p. 124
5.4.4 Conclusions from the Modeling Experiment	p. 128
5.5 Appendix A The Full Graphical Model for Assessing Transfer Probabilities	p. 128
5.6 Appendix B Probabilistic Modeling and Quantitative Assessment	p. 130
Chapter 6 Statistical Tools and Software	p. 133
6.1 Data Analysis	p. 133
6.1.1 Histograms and Lookup Tables	p. 133
6.1.1.1 Constructing a Histogram	p. 133
6.1.2 Constructing a Floating Window	p. 138
6.1.3 Estimating Low Frequencies	p. 139
6.1.4 Density Estimates	p. 140
6.1.4.1 Random Variables and Probability Density Functions	p. 140
6.1.5 Kernel Density Estimators	p. 144
6.1.5.1 What Is a Good Tuning Parameter for a Kernel Density Estimator?	p. 144
6.2 Calculating Densities by Hand	p. 145
6.3 Computer Programs	p. 148
6.3.1 The Fragment Data System (FDS)	p. 149
6.3.2 STAG	p. 149
6.3.3 Elementary	p. 149
6.3.4 CAGE	p. 150
6.4 Summary	p. 150
6.5 Appendix A	p. 151
Chapter 7 Reporting Glass Evidence	p. 153
7.1 Verbalization of a Likelihood Ratio Answer	p. 159
7.2 Sensitivity of the Likelihood Ratio Answer to Some of the Data Estimates	p. 160
7.3 The Effect of Search Procedures	p. 161
7.4 Fallacy of the Transposed Conditional	p. 162
References	p. 164
Index	p. 173

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Table of Contents