Statistics in Criminal Justice takes an approach that emphasizes the uses of statistics in research in crime and justice. This text is meant for students and professionals who want to gain a basic understanding of statistics in this field. The text takes 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, it takes a serious approach to statistics, which is relevant to the real world of research in crime and justice. This approach is meant to provide the reader with an accessible but sophisticated understanding of statistics that can be used to examine real-life criminal justice problems. The goal of the text is to give the student a basic understanding of statistics and statistical concepts that will leave the student with the confidence and the tools for tackling more complex problems on their own. Statistics in Criminal Justice is meant not only as an introduction for students but as a reference for researchers.

A number of changes have been made to the 3rd edition, including the following:

- Additional exercises at the end of each chapter

- 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, examined in a way that highlights comprehension and interpretation

- With the additional material on multivariate regression models, the text is appropriate for both undergraduate and beginning graduate statistics courses in criminal justice

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.

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. 

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 designstudies. 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 uses of statistics in research in crime and justice. This text is meant for students and professionals who want to gain a basic understanding of statistics in this field. The text takes 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, it takes a serious approach to statistics, which is relevant to the real world of research in crime and justice. This approach is meant to provide the reader with an accessible but sophisticated understanding of statistics that can be used to examine real-life criminal justice problems. The goal of the text is to give the student a basic understanding of statistics and statistical concepts that will leave the student with the confidence and the tools for tackling more complex problems on their own. Statistics in Criminal Justice is meant not only as an introduction for students but as a reference for researchers.

A number of changes have been made to the 3rd edition, including the following:

- Additional exercises at the end of each chapter

- 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, examined in a way that highlights comprehension and interpretation

- With the additional material on multivariate regression models, the text is appropriate for both undergraduate and beginning graduate statistics courses in criminal justice

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.

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. 

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 designstudies. 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.