4
Tables and graphs for monitoring temporal crime trends: Translating theory into...
source link: https://journals.sagepub.com/doi/abs/10.1177/1461355716642781
Go to the source link to view the article. You can view the picture content, updated content and better typesetting reading experience. If the link is broken, please click the button below to view the snapshot at that time.
Tables and graphs for monitoring temporal crime trends: Translating theory into practical crime analysis advice
First Published May 17, 2016
Research Article
Abstract
This article is a practical review on how to construct tables and graphs to monitor temporal crime trends. Such advice is mostly applicable to crime analysts to improve the readability of their products, but is also useful to general consumers of crime statistics in trying to identify crime trends in reported data. First, the use of percent change to identify significant changes in crime trends is critiqued, and an alternative metric based on the Poisson distribution is provided. Second, visualization principles for constructing tables are provided, and a practical example of remaking a poor table using these guidelines is shown. Finally, the utility of using time series charts to easily identify short- and long-term increases, as well as outliers in seasonal data using examples with actual crime data is illustrated.
Research off-campus without worrying about access issues. Find out about Lean Library here
References
Google Scholar
Berk, RA, MacDonald, J (2008) Overdispersion and Poisson regression. Journal of Quantitative Criminology 24(3): 269–284.
Google Scholar | Crossref | ISI
Boba Santos, R (2012) Crime Analysis with Crime Mapping (3rd edn). Thousand Oaks, CA: Sage.
Google Scholar
Boba Santos, R (2014) The effectiveness of crime analysis for crime reduction: cure or diagnosis? Journal of Contemporary Criminal Justice 30(2): 147–168.
Google Scholar | SAGE Journals | ISI
Bonkiewicz, L (2015) Bobbies and baseball players: evaluating patrol officer productivity using sabermetrics. Police Quarterly 18(1): 55–78.
Google Scholar | SAGE Journals | ISI
Braga, AA (2001) The effects of hot spots policing on crime. The Annals of the American Academy of Political and Social Science 578(1): 104–125.
Google Scholar | SAGE Journals
Brantingham, PJ, Tita, GE, Short, MB, Reid, SE (2012) The ecology of gang territorial boundaries. Criminology 50(3): 851–885.
Google Scholar | Crossref | ISI
Brimicombe, A (2012) Did GIS start a crime wave? SatNav theft and its implications for geo-information engineering. The Professional Geographer 64(3): 430–445.
Google Scholar | Crossref | ISI
Buja, A, Cook, D, Hofmann, H, Lawrence, M, Lee, E, Swayne, DF, Wickham, H (2009) Statistical inference for exploratory data analysis and model diagnostics. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367(1906): 4361–4383.
Google Scholar | Crossref | Medline | ISI
Cleveland, WS (1985) The Elements of Graphing Data. Monterey, CA: Wadsworth.
Google Scholar
Coldren, J, Huntoon, A, Medaris, M (2013) Introducing smart policing: foundations, principles, and practice. Police Quarterly 16(3): 275–286.
Google Scholar | SAGE Journals | ISI
Dabney, D (2010) Observations regarding key operational realities in a CompStat model of policing. Justice Quarterly 27(1): 28–51.
Google Scholar | Crossref | ISI
Davis, R, Ortiz, C, Euler, S, Kuykendall, L (2015) Revisiting ‘Measuring what matters’: developing a suite of standardized performance measures for policing. Police Quarterly Online First. doi: 10.1177/1098611115598990
Google Scholar | SAGE Journals | ISI
Enders, J (2007) Zebra striping: does it really help? In: Proceedings of the 19th Australasian conference on computer–human interaction, Adelaide, Australia, 28–30 November 2007, pp. 319–322. New York, NY: ACM.
Google Scholar | Crossref
Enders, J (2008) Zebra striping: more data for the case. A LIST APART. Available at: http://alistapart.com/article/zebrastripingmoredataforthecase (accessed 8 January 2015).
Google Scholar
Eterno, JA, Silverman, EB (2010) The NYPD’s Compstat: compare statistics or compose statistics? International Journal of Police Science & Management 12(3): 426–449.
Google Scholar | SAGE Journals
Feinberg, RA, Wainer, H (2011) Extracting sunbeams from cucumbers. Journal of Computational and Graphical Statistics 20(1): 793–810.
Google Scholar | Crossref | ISI
Few, S (2008) Practical rules for using color in charts. Visual Business Intelligence Newsletter, Perceptual Edge. Available at: http://www.perceptualedge.com/articles/visual_business_intelligence/rules_for_using_color.pdf (accessed 8 January 2015).
Google Scholar
Few, S (2011) Are infovis and statistical graphics really all that different? Visual Business Intelligence Newsletter, Perceptual Edge. Available at: http://www.perceptualedge.com/articles/visual_business_intelligence/rules_for_using_color.pdf (accessed 8 January 2015).
Google Scholar
Friendly, M, Kwan, E (2011) Comment. Journal of Computational and Graphical Statistics 20(1), 18–27.
Google Scholar | Crossref | ISI
Gorr, WL, Lee, YJ (2014) Early warning system for temporary crime hot spots. Journal of Quantitative Criminology 31(1): 25–47.
Google Scholar | Crossref | ISI
Guilfoyle, S (2015) Binary comparisons and police performance measurement: good or bad? Policing: A Journal of Policy and Practice 9(2): 195–209.
Google Scholar | Crossref | ISI
Harries, KD (1999) Mapping Crime: Principle and Practice. Washington, DC: U.S. Dept. of Justice, Office of Justice Programs, National Institute of Justice.
Google Scholar
Harrower, M, Brewer, C (2003) ColorBrewer.org: an online tool for selecting colour schemes for maps. The Cartographic Journal 40(1): 27–37.
Google Scholar | Crossref | ISI
Hering, S, Bair, S (2014) Characterizing spatial and chronological target selection of serial offenders. Journal of the Royal Statistical Society: Series C 63(1): 123–140.
Google Scholar | Crossref | ISI
Hyndman, RJ, Athanasopoulos, G (2014) Forecasting: Principles and Practice. OTexts.
Google Scholar
Kosara, R (2007) Visualization criticism – the missing link between information visualization and art. In: 11th International conference in information visualization, Zurich, Switzerland, IEEE Xplore digital library. 4–6 July 2007, pp. 631–636.
Google Scholar
Kosslyn, SM (1994) Elements of Graph Design, New York, NY: WH Freeman.
Google Scholar
Lee, M, Kent, T, Carswell, CM, Seidelman, W, Sublette, M (2014) Zebra-striping: visual flow in grid-based graphic design. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 58(1): 1318–1322.
Google Scholar | SAGE Journals
Lofgren, ET (2012) Visualizing results from infection transmission models: a case against ‘confidence intervals’. Epidemiology 23(5): 738–741.
Google Scholar | Crossref | Medline | ISI
Loftin, C (1986) Assaultive violence as a contagious social process. Bulletin of the New York Academy of Medicine 62(5): 550–555.
Google Scholar | Medline
Lupton, E (2010) Thinking with Type. New York, NY: Princeton Architectural Press.
Google Scholar
MacEachren, AM (2004) How Maps Work: Representation, Visualization, and Design. New York, NY: The Guilford Press.
Google Scholar
Maltz, MD (1996) From Poisson to the present: applying operations research to problems of crime and justice. Journal of Quantitative Criminology 12(1): 3–61.
Google Scholar | Crossref | ISI
Maltz, MD (2010) Look before you analyze: visualizing data in criminal justice. In: Piquero, AR, Weisburd, D (eds) Handbook of Quantitative Criminology. New York, NY: Springer, 25–52.
Google Scholar | Crossref
Manning, PK (2008) The Technology of Police: Crime Mapping, Information Technology, and the Rationality of Crime Control. New York, NY: NYU Press.
Google Scholar
Moreland, K (2009) Diverging color maps for scientific visualization. Advances in Visual Computing, Lecture Notes in Computer Science 5876: 92–103.
Google Scholar | Crossref
Osgood, DW (2000) Poisson-based regression analysis of aggregate crime rates. Journal of Quantitative Criminology 16(1): 21–43.
Google Scholar | Crossref | ISI
Payne, TC, Gallagher, K, Eck, J, Frank, J (2013) Problem framing in problem solving: a case study. Policing: An International Journal of Police Strategies and Management 36(4): 670–682.
Google Scholar | Crossref | ISI
Randol, BM (2014) Modelling the influence of organisational structure on crime analysis technology innovations in municipal police departments. International Journal of Police Science & Management 16(1): 52–64.
Google Scholar | SAGE Journals
Rogerson, PA, Sun, Y (2001) Spatial monitoring of geographic patterns: an application to crime analysis. Computers, Environment and Urban Systems 25(6): 539–556.
Google Scholar | Crossref
Roth, RE, Ross, KS, Finch, BG, Luo, W, MacEachren, AM (2013) Spatiotemporal crime analysis in U.S. law enforcement agencies: current practices and unmet needs. Government Information Quarterly 30(3): 226–240.
Google Scholar | Crossref | ISI
Sacco, VF (2005) When Crime Waves. Thousand Oaks, CA: Sage.
Google Scholar | Crossref
Sherman, LW, Weisburd, D (1995) General deterrent effects of police patrol in crime hot spots: a randomized, controlled trial. Justice Quarterly 12(4): 625–648.
Google Scholar | Crossref
Sidebottom, A, Ashby, M, Johnson, SD (2014) Copper cable theft: revisiting the price–theft hypothesis. Journal of Research in Crime and Delinquency 51(5): 684–700.
Google Scholar | SAGE Journals | ISI
Silverman, EB (1999) NYPD Battles Crime: Innovative Strategies in Policing. Boston, MA: Northeastern University Press.
Google Scholar
Spiegelhalter, D, Pearson, M, Short, I (2011) Visualizing uncertainty about the future. Science 333(6048): 1393–1400.
Google Scholar | Crossref | Medline | ISI
Tollenaar, N, van der Heijden, PGM (2013) Which method predicts recidivism best?: a comparison of statistical, machine learning and data mining predictive models, Journal of the Royal Statistical Society: Series A 176(2): 565–584.
Google Scholar | Crossref | ISI
Tufte, ER (2001) The visual display of quantitative information, Cheshire, CT: Graphics Press.
Google Scholar
Tukey, JW (1977) Exploratory Data Analysis. Reading, MA: Addison-Wesley.
Google Scholar
Wilson, OW (1957) Police Planning. Springfield, IL: Thomas.
Google Scholar
Recommend
About Joyk
Aggregate valuable and interesting links.
Joyk means Joy of geeK