Overview

An Accessible, Scenario-Driven Foundation for Statistics in Criminal Justice A solid understanding of statistics is essential for interpreting research, evaluating evidence, and making informed decisions across the social sciences. Introduction to Statistics in Criminal Justice and Criminology offers a clear and structured path to the tools and reasoning that shape empirical inquiry in the field. Emphasizing the practical purposes of statistical thinking, this student-friendly textbook explains how data is organized, described, compared, and analyzed to answer meaningful questions. Each chapter opens with a relatable scenario that frames key concepts, guiding students as they move from foundational topics—such as descriptive statistics and normal distributions—to applications including hypothesis testing, chi-square analysis, regression, ANOVA, and survival analysis. Step-by-step examples, end-of-chapter problems, and intuitive visual displays help students engage more deeply with empirical scholarship and apply a range of data-driven methods. By presenting statistics as both a practical toolkit and an essential mode of reasoning, this comprehensive guide: Balances conceptual understanding with applied calculation to support success in higher-level coursework Provides a consistent framework that connects chapter content to decision-making and research design Uses clear explanations to demystify core statistical ideas and frequently misunderstood concepts Strengthens computational literacy through a user-friendly software tool aligned with the chapter material Offers chapter summaries, structured practice opportunities, and extendable problem sets Draws on the authors' extensive experience in criminal justice, psychology, mathematics, statistics, and computer science Leverages the expertise of an interdisciplinary team spanning psychology, computer science, data science, and statistics. Requiring no advanced mathematical training, Introduction to Statistics in Criminal Justice and Criminology: A Practical Approach to Calculating, Using, and Interpreting Data is ideal for undergraduate and postgraduate courses such as Statistics in Criminal Justice, Introduction to Statistics in Criminal Justice, and Statistics for the Social Sciences. It supports required quantitative training across criminal justice curricula and prepares students in bachelor’s and graduate programs to interpret research and engage in data-informed study and practice.

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9781118559239

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Arthur J. Lurigio is Professor of Psychology and Criminal Justice and Criminology at Loyola University Chicago. Holding a PhD from Loyola University Chicago, he is a distinguished scholar with more than 500 publications and numerous awards recognizing his contributions to criminal justice research, mental health, and applied scholarship. Michael Perry is Senior Lecturer of Mathematics and Statistics at Loyola University. Holding a PhD in Engineering Science and Applied Mathematics from Northwestern University, he teaches a range of statistics courses and has published research across polymerization, public health, and quantitative modeling. Nathan M. Lutz is a pediatric psychologist and Clinical Assistant Professor at Nationwide Children’s Hospital in Columbus, Ohio. Holding a PhD in Clinical Psychology from Loyola University Chicago, his research focuses on improving outcomes for youth involved in child welfare and enhancing measurement-based behavioral health care. George K. Thiruvathukal is Professor and Chairperson of Computer Science at Loyola University Chicago and Visiting Computer Scientist at Argonne National Laboratory. Holding a PhD in Computer Science from the Illinois Institute of Technology, his research spans high-performance computing, distributed systems, empirical software engineering, artificial intelligence/machine learning, history of computing/science/technology and digital humanities/music. He is author/co-author of more than 200 publications and 6 books.

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