LITMIR.BIZ

       Preface to Second Edition

      In the Preface to the first edition of this book, it was commented that the role of statistics in forensic science is continuing to increase and that this was partly because of the debate continuing over DNA profiling which looked as if it would carry on into the foreseeable future. It now appears that the increase is continuing and perhaps at a greater rate than nine years ago. The debate over DNA profiling continues unabated. We have left the minutiae of this debate to others restricting ourselves to an overview of that particular topic. Instead, we elaborate on the many other areas in forensic science in which statistics can play a role.

There has been a tremendous expansion in the work in forensic statistics in the nine years since the first edition of this book was published. This is reflected in the increase in the size of the book. There are about 500 pages now when there were only about 250 in 1995, and the bibliography has increased from 10 pages to 20 pages. The number of chapters has increased from 8 to 14. The title remains the same yet there is more discussion of interpretation, in addition to new material on evaluation.

The first four chapters are on the same topics as in the first edition though the order of Chapters 2 and 3 on evaluation and on variation has been exchanged. The chapter on variation, the new Chapter 2, has been expanded to include many more probability distributions than mentioned in the first edition. As the subject has expanded so has the need for the use of more distributions. These have to be introduced sooner than before and hence the exchange of order with the chapter on evaluation. Chapter 4 has an additional section on the work of early twentieth‐century forensic scientists as it has gradually emerged how far ahead of their time these scientists were in their ideas. Three new chapters have then been introduced before the chapter on transfer evidence. Bayesian inference has an increasing role to play in the evaluation of evidence yet its use is still controversial and there have been some critical comments in the courts of some of its perceived uses in the legal process. Chapter 5 provides a discussion of Bayesian inference, somewhat separate from the main thrust of the book in order to emphasise its particular relevance for evidence evaluation and interpretation. Appropriate sampling procedures are becoming ever more important. With scarce resources, sampling provides a means of achieving almost the same inferences but with the expenditure of considerably less resources. It is important, though, that correct inferences are drawn from the results obtained from a sample. In some jurisdictions and some types of crime, such as that of drug smuggling in the United States, the quantity of illicit material associated with the crime is a factor in the sentencing. Again, if only a sample has been taken from the initial consignment, then correct inferences about the quantities involved have to be made. These are the topics of Chapter 6. Chapter 7 is a consequence of the expansion of the book to consider interpretation. This includes a discussion of work on case assessment and interpretation done since the appearance of the first edition. Chapter 7 also includes brief comments on various evidence types for which statistical evaluation is beginning to be developed. This is in contrast to those areas such as glass, fibres, and DNA profiling that are considerably more developed. Fibres and DNA each have chapters of their own, Chapters 12 and 13. Glass evaluation provides many examples throughout the book as it provides a context for much of what is discussed and it was felt this was better done at these places in the book rather than gathered together in a separate chapter. Chapters 8, 9, and 10 on transfer evidence, discrete data, and continuous data are updated versions of chapters on the same topics in the first edition. Correct analysis of multivariate data is essential in forensic science as such data become more prevalent, for example, in the consideration of the elemental composition of glass or the chemical composition of drugs. Multivariate analysis is discussed in Chapter 11 with a worked analysis of a two‐dimensional example. An appendix gives a brief description of the underlying mathematics of matrix algebra. Chapters 12 and 13 are the only chapters in the book that are specific to particular types of evidence, fibres and DNA profiling, respectively. Chapter 13 is a completely new chapter compared with the corresponding chapter in the first edition, such are the advances made in DNA profiling since the first edition appeared. It is still only a brief introduction to the topic. Other more specialised books, cited in Chapter 13, are recommended for the serious student of DNA profiling. The last chapter, 14, is an introduction to Bayesian networks, an exciting new topic for forensic science and evidence evaluation in general, predicted in the Preface to the first edition. A graphical representation, as provided by a Bayesian network, of the different types and pieces of evidence in a case aids considerably the understanding and analysis of the totality of the evidence. In addition to the bibliography and indexes, a list of notation has been provided at the end. It is hoped this will enable the reader to keep track of the symbolism which is a necessary part of ensuring clarity of exposition.

The role of Bayesian inference in forensic science remains controversial. In order to try to understand why this may be so, we can do no better than to quote from an eminent fibres expert who wrote:

      There may be different reasons for the obvious reluctance or scepticism connected with the adoption of Bayesian theory for presenting fibres evidence. These may include:

      (Grieve, 2001, p. 208)

      We hope that this book goes some way towards overcoming the reluctance and scepticism.

      Reference is made on occasion to probability values of statistical distributions. Rather than make reference to statistical packages and books of tables each time this is done, details of several packages are listed here instead:

      MINITAB. See http://www.minitab.com and Ryan et al. (2000).

R: This is a language and environment for statistical computing and graphics which is available in source code form as Free Software under

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