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Statistics in Criminal Justice (2nd Edition)

ISBN-10: 0387341129
ISBN-13: 9780387341125
Edition: 3rd 2007 (Revised)
List price: $109.00
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Description: 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  More...

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Book details

List price: $109.00
Edition: 3rd
Copyright year: 2007
Publisher: Springer
Publication date: 4/5/2007
Binding: Hardcover
Pages: 674
Size: 7.25" wide x 10.00" long x 1.25" tall
Weight: 3.212
Language: English

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

Sally S. Simpson (Ph.D. University of Massachusetts/Amherst) is Professor and Chair of the Department of Criminology and Criminal Justice at the University of Maryland/College Park. Ongoing research projects include a factorial survey of environmental professionals to assess regulatory attitudes toward and strategies for business, a meta-analysis of corporate crime intervention and control strategies for the Campbell Consortium Crime and Justice Group (CCJG), and the WEV study (a multi-city retrospective study of incarcerated women's experience of violence). Professor Simpson is past President of the White-Collar Crime Research Consortium and current Chair of the Crime, Law, and Deviance Section of the American Sociological Association. She is a board member of the Maryland Police Training Commission, the Children�s Justice Act Committee, and the Maryland Criminal Justice Information Advisory Board. David Weisburd is Walter E. Meyer Professor of Law and Criminal Justice and Director of the Institute of Criminology at the Hebrew University and Distinguished Professor of Administration of Justice at George Mason University. He is an elected fellow of the American Society of Criminology and of the Academy of Experimental Criminology. He is also editor of the Journal of Experimental Criminology. Professor Weisburd was part of the Yale White Collar Crime project, from which his book Crimes of the Middle Classes was developed. Professor Weisburd has also co-authored White Collar Crime and Criminal Careers and White Collar Crime Reconsidered. nbsp;

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
Defining Risks of Error: From Probabilities to a Sampling Distribution
Steps in a Statistical Test: Using the Binomial Distribution to Make Decisions about Hypotheses
Chi Square: A commonly Used Test for Nominal-Level Measures
The Normal Distribution and its Application to Statistical Tests of Significance
Comparing Means and Proportions in Two Samples
Comparing Means among More than Two Samples: Analysis of Variance
Nominal and Ordinal Measures of Association
Measuring Association for Interval Level Data: Pearson's Correlation Coefficient
An Introduction to Bivariate Regression
Multivariate Regression
An Introduction to Logistic Regression
Special Topics: Confidence Intervals
Special Topics: Statistical Power

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