Recent misconceptions about the "database search problem": a probabilistic analysis using Bayesian networks

This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.

Iowa Prison Population Forecast FY 2004-2014

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2005-2015

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.