Encyclopedia of Criminology and Criminal Justice

2014 Edition
| Editors: Gerben Bruinsma, David Weisburd

History of the Statistics of Crime and Criminal Justice

  • Michael D. Maltz
  • Kathleen Frey
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-5690-2_250


This entry provides an account of the history of statistics and its relation to criminal justice and criminology. It describes how the “Law of Errors,” initially based on astronomical observations, was adopted to explain “social physics” and in particular, the relative constancy of crime. Analytic methods that were developed to uncover patterns in data, which were not apparent prior to the utilization of the new methods, are described. Frequentist and Bayesian views of statistics are discussed, as well as issues surrounding some of the analytical methods used in criminology and criminal justice, including the concept of “statistical significance”; these issues are often glossed over by those who apply them.


When a researcher in criminology and criminal justice does statistical analysis nowadays, all too often it goes like this. S/he:
  • Gets permission to access a data set – for example, the National Longitudinal Survey of Youth (NLSY), the National Longitudinal...

This is a preview of subscription content, log in to check access.



The authors thank Laura Dugan for her helpful comments. This entry borrows liberally from Maltz (1994a, b).

Recommended Reading and References

  1. Anwar S, Loughran T (2011) Testing a Bayesian learning theory of deterrence among serious juvenile offenders. Criminology 49:667–698Google Scholar
  2. Block C, Block R (1995) Trends, risks, and interventions in lethal violence: proceedings of the third annual spring symposium of the Homicide Research Working Group. National Institute of Justice, US Department of Justice, Washington, DCGoogle Scholar
  3. Cohen J (1990) Things I have learned (so far). Am Psychol 45:1304–1312Google Scholar
  4. Cohen J (1994) The earth is round (p <.05). Am Psychol 49:997–1003Google Scholar
  5. Duncan OD (1984) Notes on social measurement: historical and critical. Russell Sage, New YorkGoogle Scholar
  6. Freedman DA (1985) Statistics and the scientific method. In: Mason WM, Fienberg SE (eds) Cohort analysis in the social sciences: beyond the identification problem. Springer, New York, pp 343–366Google Scholar
  7. Gottfredson M, Hirschi T (1990) A general theory of crime. Stanford University Press, StanfordGoogle Scholar
  8. Hacking I (1975) The emergence of probability. Cambridge University Press, CambridgeGoogle Scholar
  9. Hacking I (1990) The taming of chance. Cambridge University Press, CambridgeGoogle Scholar
  10. Hacking I (1991) How shall we do the history of statistics? In: Burchell G, Gordon C, Miller P (eds) The Foucault effect: studies in governmentality. University of Chicago Press, Chicago, pp 181–195Google Scholar
  11. Lehrer J (2010) The truth wears off. New Yorker. 13 Dec 2010; available online at http://www.newyorker.com/reporting/2010/12/13/101213fa_fact_lehrer
  12. Lieberson S (1985) Making it count: the improvement of social research and theory. University of California Press, Berkeley, CaliforniaGoogle Scholar
  13. Lindley DV (1992) Introduction to Good (1952) rational decisions. In: Kotz S, Johnson NL (eds) Breakthroughs in statistics, volume I: foundations and basic theory. Springer, New York, pp 359–364Google Scholar
  14. Loftus GR (1993) A picture is worth a thousand p-values: on the irrelevance of hypothesis testing in the computer age. Behav Res Meth Instrum Comp 25:250–256Google Scholar
  15. Maltz M D (1984) Recidivism. Academic, Orlando. Internet version published in 2001; available at http://osu.academia.edu/MichaelMaltz
  16. Maltz MD (1994a) Deviating from the mean: the declining significance of significance. J Res Crime Delinq 31:434–463Google Scholar
  17. Maltz MD (1994b) Operations research in studying crime and justice: its history and accomplishments. In: Pollock SM, Barnett A, Rothkopf MH (eds) Operations research and the public sector (Chapter 7), Volume 6 of the handbooks in operations research and management science, edited by GL Nemhauser and AHG Rinnooy Kan. Elsevier, Amsterdam/Netherlands, pp. 201–262Google Scholar
  18. Maltz MD, Gordon AC, Friedman W (1991) Mapping crime in its community setting: event geography analysis. Springer, New York. Internet version published in 2000; available at http://osu.academia.edu/MichaelMaltzGoogle Scholar
  19. McGrayne SB (2011) The theory that would not die: how Bayes’ rule cracked the Enigma code, hunted down Russian submarines & emerged triumphant from two centuries of controversy. Yale University Press, New HavenGoogle Scholar
  20. Noaks L, Wincup E (2004) Criminological research: understanding qualitative methods. Sage, LondonGoogle Scholar
  21. Park R, Burgess E (1925) The city. University of Chicago Press, ChicagoGoogle Scholar
  22. Porter T (1986) The rise of statistical thinking. Princeton University Press, PrincetonGoogle Scholar
  23. Sampson RJ, Laub JH (1993) Crime in the making: pathways and turning points through life. Harvard University Press, CambridgeGoogle Scholar
  24. Savage S (2009) The flaw of averages: why we underestimate risk in the face of uncertainty. Wiley, New YorkGoogle Scholar
  25. Shaw C (1930) The jack roller. University of Chicago Press, ChicagoGoogle Scholar
  26. Shaw C, McKay H (1942) Juvenile delinquency and urban areas. University of Chicago Press, ChicagoGoogle Scholar
  27. Sherman LW, Weisburd D (1995) General deterrent effects of police patrol in crime hot spots: a randomized, controlled trial. Justice Quart 25:625–648Google Scholar
  28. Stigler SM (1986) The history of statistics: the measurement of uncertainty before 1900. Harvard University Press, CambridgeGoogle Scholar
  29. Tukey JW (1992) The future of data analysis. In: Kotz S, Johnson NL (eds) Breakthroughs in statistics, volume II: methodology and distribution. Springer, New York, pp 408–452Google Scholar
  30. Tukey JW (1977) Exploratory data analysis. Addison-Wesley Publishing Company, Reading, MassachusettsGoogle Scholar
  31. Wilkinson L, Task Force on Statistical Inference (1999) Statistical methods in psychology journals: guidelines and explanations. Am Psychol 54:594–604Google Scholar
  32. Ziliak S, McClosky D (2008) The cult of statistical significance: how the standard error costs us jobs, justice, and lives. University of Michigan Press, Ann ArborGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Sociology, Criminal Justice Research CenterThe Ohio State UniversityColumbusUSA
  2. 2.Emeritus, Department of Criminal Justice and Department of Information and Decision SciencesUniversity of Illinois at ChicagoChicagoUSA
  3. 3.Department of Criminology and Criminal JusticeUniversity of MarylandCollege ParkUSA