Michael J. Devalve

Statistical Analyses for Criminal Justice and Criminology (eBook, ePUB)

A Conceptual Introduction

• Format: ePub

Produktbeschreibung

This book is a how-to guide on statistical analyses designed for undergraduates and others new to the subject. It uses a conceptual framework, starting with the most basic concepts of statistics and moving up through the capacity to perform bivariate regression.

Written in an easy-going and clear style, it uses policing data to illustrate concepts. Easily identified Main Take-Aways and Key Terms features aid student understanding. Designed to combat the fear of mathematics and statistics often held by students in the social sciences, plain verbiage, multiple examples, and clear demonstrations combine to achieve the actualization and proper contextualized use of univariate and bivariate statistics. This work also serves as a launching pad for further study in statistics.

As an accessible introduction to statistics in criminal justice and criminology, this text will appeal to both students and instructors in introductory criminal justice and criminology statistics courses.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 194
• Erscheinungstermin: 27. Juni 2024
• Englisch
• ISBN-13: 9781040042410
• Artikelnr.: 70759317

Autorenporträt

Michael J. DeValve is an associate professor in the Department of Criminal Justice at Bridgewater State University. His scholarly focus is on the nexus of justice and love. In addition, DeValve has written about justice organization capacity building and conflict resolution. He is the author of numerous works, including A Different Justice: Love and the Future of Criminal Justice Practice in America and Personal Ethics and Ordinary Heroes: The Social Context of Morality (Routledge, 2021). He has been teaching analyzing criminal justice data for many years using the concepts in this text.

Inhaltsangabe

1. Introduction and Basic Concepts 2. Presenting Data 3. Centrality 4.
Variation and Dispersion 5. Basic Probability and the Normal Curve 6. The
Central Limit Theorem and Sampling 7. Point Estimates and Confidence
Intervals 8. The Reasoning Behind Hypothesis Testing 9. Bivariate
Hypothesis Testing: t Tests 10. Bivariate Hypothesis Testing: ANOVA 11.
Bivariate Hypothesis Testing: Measures of Correlation 12. An Introduction
to Bivariate Linear Regression 13. Nonparametric Tests of Relation and
Measures of Association

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1. Introduction and Basic Concepts 2. Presenting Data 3. Centrality 4. Variation and Dispersion 5. Basic Probability and the Normal Curve 6. The Central Limit Theorem and Sampling 7. Point Estimates and Confidence Intervals 8. The Reasoning Behind Hypothesis Testing 9. Bivariate Hypothesis Testing: t Tests 10. Bivariate Hypothesis Testing: ANOVA 11. Bivariate Hypothesis Testing: Measures of Correlation 12. An Introduction to Bivariate Linear Regression 13. Nonparametric Tests of Relation and Measures of Association