Statistical methodology plays a key role in ensuring that DNA evidence is collected, interpreted, analyzed and presented correctly. With the recent advances in computer technology, this methodology is more complex than ever before. There are a growing number of books in the area but none are devoted to the computational analysis of evidence. This book presents the methodology of statistical DNA forensics with an emphasis on the use of computational techniques to analyze and interpret forensic evidence.
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Wing Kam Fung – Department of Statistics and Actuarial Science, University of Hong Kong
With 20 years of lecturing and research experience, Professor Fung has been invited many times to give talks at workshops and international conferences. He has written over 130 papers in statistics, DNA profiling and forensic science, and is currently an Associate Editor for 4 statistical journals.
Yue-Qing Hu – Department of Mathematics, Southeast University
An Associate Professor, Yue-Qing Hu has published over 30 refereed papers, a number of these with Wing Kam Fung.
Since the introduction of DNA evidence to the criminal justice system in the late 1980s, statistical methodologies have governed the collection, analysis and interpretation of forensic data. The employment of advanced computer technologies has enabled DNA evidence to be employed in increasingly complex procedures, and this, in turn, has facilitated the use of more intricate and specialized statistical techniques.
Statistical DNA Forensics sets out to provide a practical guide to the analysis of DNA evidence. The authors present an overview of the essential statistical methodology and computational techniques used in analyzing DNA evidence. Basic genetics and elementary statistics are introduced, enabling readers from either discipline to understand complex forensic cases and make use of the advanced topics presented.
The book:
Statistical DNA Forensics: Theory, Methods and Computation takes a software-based approach to the subject, and makes essential reading for students, researchers and practitioners in forensic science, genetics and applied statistics.
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