8. Classification of Observations

  1. Franco Taroni1,
  2. Silvia Bozza2,
  3. Alex Biedermann1,
  4. Paolo Garbolino3 and
  5. Colin Aitken4

Published Online: 9 APR 2010

DOI: 10.1002/9780470665084.ch8

Data Analysis in Forensic Science: A Bayesian Decision Perspective

Data Analysis in Forensic Science: A Bayesian Decision Perspective

How to Cite

Taroni, F., Bozza, S., Biedermann, A., Garbolino, P. and Aitken, C. (2010) Classification of Observations, in Data Analysis in Forensic Science: A Bayesian Decision Perspective, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470665084.ch8

Author Information

  1. 1

    School of Criminal Justice, University of Lausanne, Switzerland

  2. 2

    Department of Statistics, University Ca' Foscari, Venice, Italy

  3. 3

    Faculty of Arts and Design, IUAV University, Venice, Italy

  4. 4

    School of Mathematics, University of Edinburgh, UK

Publication History

  1. Published Online: 9 APR 2010
  2. Published Print: 9 APR 2010

ISBN Information

Print ISBN: 9780470998359

Online ISBN: 9780470665084

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Keywords:

  • continuous data;
  • discrete data;
  • Forensic scientists;
  • non-normal distributions;
  • populations;
  • probability distribution

Summary

Forensic scientists are routinely faced with the problem of classifying an observation into one of several populations on the basis of the available measurements of some attributes. A fundamental assumption throughout this chapter is that there are a finite number of populations from which the observation may have come, and that each population is characterized by a probability distribution of the measurements. In some cases the populations are completely specified in the sense that the probability distributions are assumed known; in other cases only the form of each distribution is specified, but parameters need to be estimated. The chapter focuses on comparison of models using continuous data and discrete data. It describes the two populations of bank notes, the first given by bank notes coming from drug trafficking, and the second given by bank notes in general circulation. The chapter also provides a note on the multivariate continuous data.

Controlled Vocabulary Terms

continuous data; discrete data; probability distribution