Handbook of Quantitative Criminology by Alex R. Piquero, David Weisburd

By Alex R. Piquero, David Weisburd

The guide of Quantitative Criminology is designed to be the authoritative quantity on methodological and statistical concerns in criminology and legal justice. At a time while this box is gaining in sophistication and working with ever extra complicated empirical difficulties, this quantity seeks to supply readers with a transparent and recent advisor to quantitative criminology. Authored by way of major students in criminology/criminal justice, the Handbook comprises 35 chapters on issues within the following key components: (1) study layout, (2) experimental tools, (3) tools for overcoming information boundaries, (4) cutting edge descriptive tools, (5) estimation concepts for conception and coverage, (6) issues in a number of regression, and (7) new instructions in statistical research. The contributions are written to be obtainable to readers with a uncomplicated history in facts and learn equipment, yet in addition they supply a leading edge view of statistical and methodological difficulties and questions. This ebook stands out as the go-to booklet for brand new and complicated tools within the box that might offer overviews of the main matters, with examples and figures as warranted, for college students, school, and researchers alike.

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Int J Forecast 19(4):595–601 Field S (1992) The effect of temperature on crime. Br J Criminol 32(3):340–351 Forrester D, Chatterton M, Pease K (1988) The Kirkholt burglary prevention project, Rochdale (No. 13). Crime Prevention Unit (Home Office), London Fotheringham AS, Brunsdon C, Charlton M (2002) Geographically weighted regression. Wiley, Chichester, UK Fotheringham SA, Brunsdon C (2004) Some thoughts on inference in the analysis of spatial data. Int J Geogr Inf Sci 18(5):447–457 Getis A, Ord JK (1992) The analysis of spatial association by use of distance statistics.

4 As will be shown, they are very useful in analyzing criminal justice data and can provide new insights that would not have been possible using standard statistical methods. 5 In most of these cases, I use examples of my own work and techniques developed specifically for these examples. They are not unique or very complicated; others have used similar techniques for similar problems. It should be noted, however, that because different data sets have different variables and different relationships among their variables, there is no standard means of visualizing data.

4). There is also a need to determine whether a zero is a true zero or a missing datum. For example, Fig. 5 shows the number of Index crimes8 reported to the FBI by the Bibb County (Georgia) Police Department. As can be seen, there are a number of times when the crime counts were zero: 6A similar strategy was used in cleaning FBI-collected arrest data (Maltz and Weiss 2007). the field contains five characters, as it might for the crime of larceny in large cities, then the missing value might be 99999.

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