Statistics In Criminology And Criminal Justice Analysis And Interpretation

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.

Criminal Justice / Law Enforcement

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.

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

This book provides hands-on guidance for researchers and practitioners in criminal justice and criminology to perform statistical analyses and data visualization in the free and open-source software R. It offers a step-by-step guide for beginners to become familiar with the RStudio platform and tidyverse set of packages. This volume will help users master the fundamentals of the R programming language, providing tutorials in each chapter that lay out research questions and hypotheses centering around a real criminal justice dataset, such as data from the National Survey on Drug Use and Health, National Crime Victimization Survey, Youth Risk Behavior Surveillance System, The Monitoring the Future Study, and The National Youth Survey. Users will also learn how to manipulate common sources of agency data, such as calls-for-service (CFS) data. The end of each chapter includes exercises that reinforce the R tutorial examples, designed to help master the software as well as to provide practice on statistical concepts, data analysis, and interpretation of results. The text can be used as a stand-alone guide to learning R or it can be used as a companion guide to an introductory statistics textbook, such as Basic Statistics in Criminal Justice (2020).

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.

Statistical analysis is critical in criminal justice. Professionals in the field must be diligent producers of research to assist policy makers in evaluating program and policy proposals. The key to understanding statistical analysis is by applying the concepts, methodology, and statistical procedures taught in the classroom. Written for undergraduates with little or no background in statistics, the third edition of Statistical Analysis in Criminal Justice and Criminology continues to focus on students’ understanding of fundamental analysis. It is premised on active learning utilizing common statistical tools to analyze crime data, avoiding the comprehensive approach common to many statistics texts. Authors draw from longtime classroom experience to present complex theories in approachable ways. Exercises move from an initial step through the application of concepts explained in each chapter before insights on interpreting the results in a meaningful way is provided. New to this edition is the inclusion of both SPSS and Excel criminal justice data sets used to complete end-of-chapter exercises and analyses. This distinctive offering enables readers to develop their skills with the program most accessible to them.