Permutation Statistical Methods For Criminology And Criminal Justice

This book takes a unique approach to explaining permutation statistical methods for advanced undergraduate students, graduate students, faculty, researchers, and other professionals interested in the areas of criminology or criminal justice. The book integrates permutation statistical methods with a wide range of classical statistical methods. It opens with a comparison of two models of statistical inference: the classical population model espoused by J. Neyman and E. Pearson and the permutation model first introduced by R.A. Fisher and E.J.G. Pitman. Numerous comparisons of permutation and classical statistical methods are illustrated with examples from criminology and criminal justice and supplemented with a variety of R scripts for ease of computation. The text follows the general outline of an introductory textbook in statistics with chapters on central tendency, variability, one-sample tests, two-sample tests, matched-pairs tests, completely-randomized analysis of variance, randomized-blocks analysis of variance, simple linear regression and correlation, and the analysis of goodness of fit and contingency. Unlike classical statistical methods, permutation statistical methods do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity, depend solely on the observed data, and do not require random sampling, making permutation statistical methods ideal for analyzing criminology and criminal justice databases. Permutation methods are relatively new in that it took modern computing power to make them available to those working in criminology and criminal justice research. The book contains detailed examples of permutation analyses. Each analysis is paired with a conventional analysis; for example, a permutation test of the difference between experimental and control groups is contrasted with Student's two-sample $t$ test. An added feature is the inclusion of multiple historical notes on the origin and development of both parametric and conventional tests and measures. Designed for an audience with a basic statistical background and a strong interest in parametric and non-parametric statistics, the book can easily serve as a textbook for undergraduate and graduate students in criminology, criminal justice, or sociology, as well as serving as a research source for faculty, researchers, and other professionals in the area of criminology. No statistical training beyond a first course in statistics is required, but some knowledge of, or interest in, criminology or criminal justice is assumed.

The updated Fourth Edition of Statistics in Criminology and Criminal Justice: Analysis and Interpretation provides criminal justice students with a firm knowledge base in the theory and application of statistical analysis. A great introduction to the theory and practice of statistics, the Fourth Edition focuses on data collection, knowing which statistics to use with what data, how to interpret output of SPSS (an IBM company), explanations and demonstrations of statistical procedures, why procedures give the results they do, how to interpret the output of statistical analyses, and more. Each chapter has been updated to include new information on statistical output, revised data files, additional data sets, and extensive use of flowcharts to increase students' confidence in analyzing and conducting statistical research.

Thoroughly updated and revised, the Third Edition of Statistics in Criminology and Criminal Justice: Analysis and Interpretation provides criminal justice students with a firm knowledge base in the theory and application of statistical analyses. Students will be introduced to methods of identifying and classifying data, followed by explanations and demonstrations of statistical procedures. They will learn what statistical techniques are appropriate for particular data, why procedures give the results they do, and how to interpret the output of statistical analyses.

Statistics in Criminology and Criminal Justice, Fifth Edition is the ideal text for undergraduate and graduate-level statistics courses in criminal justice, criminology, and sociology programs. It teaches students how to collect, organize and record, analyze, interpret, and apply the statistical information.

Criminal Justice / Law Enforcement

The only book that specifically focuses on statistics in criminology and criminal justice, Statistical Methods for Criminology and Criminal Justice can be used at either the introductory or intermediate levels. The text contains in-depth coverage of descriptive statistics, including graphical displays of data and exploratory data analysis. It offers a detailed explanation of multivariate statistics that is easy to comprehend and covers bivariate and multivariate analysis of data with binary dependent variables.

This book provides the student, researcher or practitioner with the tools to understand many of the most commonly used advanced statistical analysis tools in criminology and criminal justice, and also to apply them to research problems. The volume is structured around two main topics, giving the user flexibility to find what they need quickly. The first is “the general linear model” which is the main analytic approach used to understand what influences outcomes in crime and justice. It presents a series of approaches from OLS multivariate regression, through logistic regression and multi-nomial regression, hierarchical regression, to count regression. The volume also examines alternative methods for estimating unbiased outcomes that are becoming more common in criminology and criminal justice, including analyses of randomized experiments and propensity score matching. It also examines the problem of statistical power, and how it can be used to better design studies. Finally, it discusses meta analysis, which is used to summarize studies; and geographic statistical analysis, which allows us to take into account the ways in which geographies may influence our statistical conclusions.

Using Statistics in Criminal Justice is designed to be an accessible, readable introduction to statistics, written with the criminal justice student in mind. The text teaches students not only how to engage in basic statistical analysis, but, more importantly, how they might use statistics in real and helpful ways. The book is designed for students to understand that statistics is a mechanism by which we take a picture of the world around us. Murray starts by taking students through the steps of creating a rough outline with basic descriptive statistics, then moves to providing more detail and clarity with sampling and inferential statistics. Finally, the author explains using multivariate techniques to fill in the details of the picture, making it more and more indicative of reality. Features: Carefully structured text provides an overview of concepts for each chapter, and explains how concepts in the book interrelate. Multiple examples for each analysis Practice questions at the end of each chapter Clearly ties in theory, methods and statistics , linking concepts from other courses Gives numerous step-by-step examples of analyses Information on how to use in a variety of software: STATA, SPSS and Excel to better accommodate various approaches Conversational tone with real world examples Application to professionals in criminal justice, not just undergraduate students Chapter on Evaluation Research gives students more marketable skills Workbook will be available on line with additional practice problems to use with statistical software