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Statistics in Criminology and Criminal JusticeAuthors: Jeffery T Walker, Sean Maddan
, including the Preface and complete table of contents and see why this book is the clear choice for undergraduate statistics courses.
It’s critical for students to learn how to collect and analyse social science data to understand the nature of crime and theories of why crime occurs. Statistics in Criminology and Criminal Justice: Analysis and Interpretation does just that. It teaches how to collect, organise, record, analyse, interpret, and apply statistical information to prepare students for their careers or graduate study. With nearly 40 years of combined teaching experience and 15 years of revising editions, Drs. Walker and Maddan have crafted an engaging and understandable presentation of theory and the application of statistical analysis in this modernised Fifth Edition. They focus on data collection, knowing which statistics to use with what data, how to interpret output of SPSS (an IBM company), explanations and demonstrations of statistical procedures, why procedures give the results they do, how to interpret the output of statistical analyses, and more.
Problem-solving is a core element to understanding and applying statistical analysis, and the fifth edition of Statistics in Criminology and Criminal Justice is unparalleled in the tools it provides to unlock this complex subject. Exercises have been moved from the end of chapters to be interwoven with the material, allowing students immediate practice of key concepts, equations, and calculations, and a new online Student Practice Workbook offers additional opportunities to practice and learn-by-doing.
TABLE OF CONTENTS
Chapter 2 Variables and Measurement
Chapter 3 Understanding Data Through Organization
Chapter 4 Measures of Central Tendency
Chapter 5 Measures of Dispersion
Chapter 6 The Form of a Distribution
Chapter 7 Introduction to Bivariate Descriptive Statistics
Chapter 8 Measures of Existence and Statistical Significance
Chapter 9 Measures of Strength of a Relationship
Chapter 10 Measures of Direction and Nature of a Relationship
Chapter 11 Introduction to Inferential Analysis
Chapter 12 Hypothesis Testing
Chapter 13 Hypothesis Tests
Chapter 14 Analysis of Variance (ANOVA)
Chapter 15 Introduction to Multivariate Statistics
Chapter 16 Multiple Regression I: Ordinary Least Squares Regression
Chapter 17 Multiple Regression II: Limited Dependent Variables
Chapter 18 Factor Analysis and Structural Equation Modeling
Chapter 19 Putting It All Together
Appendix A Math Review and Practice Test
Appendix B Statistical Tables
Appendix C The Greek Alphabet
Appendix D Variables in Data Sets