Statistics in Criminal Justice introduces basic statistics and statistical concepts in a building-block method with each chapter building in sophistication to prepare for the concepts that follow. While emphasizing comprehension and interpretation, rather than computation, the book takes a serious approach to statistics, which is tailored to the real world of crime and justice. This provides the reader with an accessible but sophisticated understanding of statistics as applied to real-life criminal justice problems. 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 additional material on multivariate regression models. The book is designed for undergraduate and beginning graduate statistics courses in criminal justice, and as a reference for researchers.

Autorentext

David Weisburd (Ph.D., Yale University) is a leading researcher and scholar in the field of criminal justice. He is Professor of Criminology at the Hebrew University Law School in Jerusalem and is a professor in the Department of Criminology and Criminal Justice at the University of Maryland. Professor Weisburd serves as a senior fellow at the Police Foundation in Washington DC, and is a member of the National Academy of Sciences Panel on Police Practices and Polices and the steering committee of the Campbell Crime and Justice Coordinating Group.

Chester Britt (Ph.D, University of Arizona) is a researcher and scholar in the field of criminology. He is Associate Professor in the Administration of Justice Department at Arizona State University West. Professor Britt is the editor for Justice Quarterly. He has published more than twenty scientific articles and book chapters on issues related to the demography of crime, criminal careers, criminal case processing, and statistics.

Klappentext

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

Inhalt

Introduction: Statistics as a Research Tool.- Measurement: The Basic Building Block of Research.- Representing and Displaying Data.- Describing the Typical Case: Measures of Central Tendency.- How Typical Is the Typical Case?: Measuring Dispersion.- The Logic of Statistical Inference: Making Statements About Populations from Sample Statistics.- Defining the Observed Significance Level of a Test: A Simple Example Using the Binomial Distribution.- Steps in a Statistical Test: Using the Binomial Distribution to Make Decisions About Hypotheses.- Chi-Square: A Test Commonly Used for Nominal-Level Measures.- The Normal Distribution and Its Application to Tests of Statistical Significance.- Comparing Means and Proportions in Two Samples.- Comparing Means Among More Than Two Samples: Analysis of Variance.- Measures of Association for Nominal and Ordinal Variables.- Measuring Association for Interval-Level Data: Pearson's Correlation Coefficient.- An Introduction to Bivariate Regression.- Multivariate Regression.- Multivariate Regression: Additional Topics.- Logistic Regression.- Multivariate Regression with Multiple Category Nominal or Ordinal Measures: Extending the Basic Logistic Regression Model.- Special Topics: Confidence Intervals.- Special Topics: Statistical Power.