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The precision, accuracy and efficiency of geographic profiling predictions: a simple heuristic versus mathematical algorithms

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
  • Craig Bennell
  • K Emeno
  • Brent Snook
  • Paul Taylor
  • Alasdair Goodwill
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<mark>Journal publication date</mark>2009
<mark>Journal</mark>Crime Mapping: A Journal of Research and Practice
Issue number2
Volume1
Number of pages20
Pages (from-to)65-84
Publication StatusPublished
<mark>Original language</mark>English

Abstract

This study compared the precision, accuracy, and efficiency of geographic profiles made by students to those made by mathematical algorithms. After making predictions on 20 maps, each depicting a different offense series, nearly half of the sampled students were instructed that "the majority of offenders commit offenses close to home". All of the students were then asked to make predictions on a different set of 20 maps. Seven different mathematical algorithms, several derived from a new Bayesian journey-to-crime estimation method, were also applied to the 40 maps. Results showed that informing students about the "distance decay heuristic" increased the precision of their predictions, but these predictions were not as accurate or efficient as those made by most of the algorithmic procedures. Implications of these results for the field of geographic profiling are discussed.