Chapter 3. Concepts of Statistical Science and Decision Theory

  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.ch3

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) Concepts of Statistical Science and Decision Theory, in Data Analysis in Forensic Science: A Bayesian Decision Perspective, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470665084.ch3

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:

  • concepts of statistical science and decision theory;
  • random variables and distribution functions;
  • measures of location and variability;
  • multiple random variables - multiple observations, characteristics measured on item or person;
  • statistical inference and decision theory - problems towards which statistical studies are being addressed;
  • utility function construction;
  • Bayesian paradigm, probabilistic modeling - providing probability of hypothetical data set;
  • single application of Bayes' theorem - to entire sets of data;
  • Markov Chain Monte Carlo methods (MCMC);
  • Bayesian decision theory, Bayesian statistical inference as a decision problem

Summary

This chapter contains sections titled:

  • Random Variables and Distribution Functions

  • Statistical Inference and Decision Theory

  • The Bayesian Paradigm

  • Bayesian Decision Theory

  • R Code