This introductory textbook takes a building-block approach that emphasizes the application and interpretation of statistics in research in crime and justice. This text is meant for both students and professionals who want to gain a basic understanding of common statistical methods used in criminology and criminal justice before advancing to more complex statistical analyses in future volumes. This book emphasizes comprehension and interpretation. As the statistical methods discussed become more complex and demanding to compute, it integrates statistical software. It provides readers with an accessible understanding of popular statistical programs used to examine real-life crime and justice problems (including SPSS, Stata, and R). In addition, the book includes supplemental resources such as a glossary of key terms, practice questions, and sample data. Basic Statistics in Criminology and Criminal Justice aims to give students and researchers a core understanding of statistical concepts and methods that will leave them with the confidence and tools to tackle the statistical problems in their own research work.

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.

Statistics in Criminal Justice takes an approach that emphasizes the application and interpretation of statistics in research in crime and justice. This text is meant for both students and researchers who want to gain a basic understanding of common statistical methods used in this field. In general, the text relies on a building-block approach, meaning that each chapter helps to prepare the student for the chapters that follow. It also means that the level of sophistication of the text increases as the text progresses. Throughout the text there is an emphasis on comprehension and interpretation, rather than computation. However, as the statistical methods discussed become more complex and demanding to compute, there is increasing use and integration of statistical software. This approach is meant to provide the reader with an accessible, yet sophisticated understanding of statistics that can be used to examine real-life criminal justice problems with popular statistical software programs. The primary goal of the text is to give students and researchers a basic understanding of statistical concepts and methods that will leave them with the confidence and the tools for tackling more complex problems on their own. New to the 4th Edition * New chapter on experimental design and the analysis of experimental data. * New chapter on multi-level models, including growth-curve models. * New computer exercises throughout the text to illustrate the use of both SPSS and Stata. * Revision of exercises at the end of each chapter that places greater emphasis on using statistical software. * Additional resources on the text's web site for instructors and students, including answers to selected problems, syntax for replicating text examples in SPSS and Stata, and other materials that can be used to supplement the use of the text.

"Statistics in Criminal Justice" takes an approach that emphasizes the application and interpretation of statistics in research in crime and justice. This text is meant for both students and researchers who want to gain a basic understanding of common statistical methods used in this field. In general, the text relies on a building-block approach, meaning that each chapter helps to prepare the student for the chapters that follow. It also means that the level of sophistication of the text increases as the text progresses. Throughout the text there is an emphasis on comprehension and interpretation, rather than computation. However, as the statistical methods discussed become more complex and demanding to compute, there is increasing use and integration of statistical software. This approach is meant to provide the reader with an accessible, yet sophisticated understanding of statistics that can be used to examine real-life criminal justice problems with popular statistical software programs. The primary goal of the text is to give students and researchers a basic understanding of statistical concepts and methods that will leave them with the confidence and the tools for tackling more complex problems on their own.

New to the 4th Edition

.New chapteron experimental design and the analysis of experimental data.

.New chapteron multi-level models, including growth-curve models.

. New computer exercises throughout the text to illustrate the use of both SPSS and Stata.

. Revision of exercises at the end of each chapter that places greater emphasis on using statistical software.

. Additional resources on the text s web site for instructors and students, including answers to selected problems, syntax for replicating text examples in SPSS and Stata, and other materials that can be used to supplement the use of the text."

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.

This introductory textbook takes a building-block approach that emphasizes the application and interpretation of statistics in research in crime and justice. This text is meant for both students and professionals who want to gain a basic understanding of common statistical methods used in criminology and criminal justice before advancing to more complex statistical analyses in future volumes. This book emphasizes comprehension and interpretation. As the statistical methods discussed become more complex and demanding to compute, it integrates statistical software. It provides readers with an accessible understanding of popular statistical programs used to examine real-life crime and justice problems (including SPSS, Stata, and R). In addition, the book includes supplemental resources such as a glossary of key terms, practice questions, and sample data. Basic Statistics in Criminology and Criminal Justice aims to give students and researchers a core understanding of statistical concepts and methods that will leave them with the confidence and tools to tackle the statistical problems in their own research work.

NEW AND REVISED THIRD EDITION

This book introduces basic statistics and statistical concepts, with each chapter building in sophistication to prepare for the concepts that follow. Emphasizing comprehension and interpretation over computation, the book still takes a serious approach to statistics, tailored to the real world of crime and justice. The updated and expanded 3rd edition includes additional chapter-end exercises; expanded computer exercises that can be performed in the Student Version of SPSS; extended discussion of multivariate regression models, including interaction and non-linear effects; a new chapter on multinomial and ordinal logistic regression models, designed for comprehension and interpretation; and new material on multivariate regression models.

"One course that students always put off until they are nearing the completion of their degree requirements is statistics. The fear is that the material is either too difficult or the book doesn't make sense. Although as teachers we can do little about the former, we can do much about the latter, and Weisburd and Britt have done just that. Statistics in Criminal Justice is precisely the book I wish I learned statistics with when I was a student. It presents readers with the basic tools needed to be a consumer and user of criminal justice research, includes many examples spanning a wide range of criminal justice/criminological topics, and the end-of-chapter study questions and computer exercises reinforce key concepts. To the authors' credit, this text goes even farther by introducing the reader to more advanced forms of regression-based analyses. As such, the book can and should be read by undergraduate students starting off in higher education, graduate students embarking on their academic careers, and even seasoned faculty who every now and again need to recall a formula or brush up on some matters. After reading Statistics in Criminal Justice, I am sure you will join me in thanking these two first-rate scholars for taking the time to teach us statistics in an enjoyable and effective manner."

-Alex R. Piquero, Presidential Scholar & Professor, University of Maryland-College Park