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Statistics for Criminology and Criminal Justice

Medium: Buch
ISBN: 978-1-4833-7845-9
Verlag: Sage Publications Ltd.
Erscheinungstermin: 05.05.2015
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A Beginner’s Guide to Statistics in Criminology and Criminal Justice Careers



Statistics for Criminology and Criminal Justice, Second Edition is an introductory statistics text for undergraduate criminology and criminal justice majors. The topics and engaging presentation style are targeted to students who have a basic background in algebra but who have had little or no exposure to the study of statistics. The overarching goals of the book are to demonstrate to students that statistics used in criminal justice can be enlightening and eye-opening and, that pre-conceived notions of their academic inadequacies coming into the course are false.



The fully updated Second Edition includes new learning objectives and learning checks to help guide students through the material and ensure content understanding and retention. Coverage of the fundamental areas in statistics begins with descriptive statistics, moves into probability, and ends with regression to make the content easier for students to follow. By use of real data and research, emphasis is placed on balancing thoroughness with ease of understanding in order to show students the importance and relevance of statistics in their future criminal justice careers.

Produkteigenschaften


  • Artikelnummer: 9781483378459
  • Medium: Buch
  • ISBN: 978-1-4833-7845-9
  • Verlag: Sage Publications Ltd.
  • Erscheinungstermin: 05.05.2015
  • Sprache(n): Englisch
  • Auflage: 2. Auflage 2015
  • Produktform: Kartoniert
  • Gewicht: 739 g
  • Seiten: 432
  • Format (B x H x T): 189 x 230 x 25 mm
  • Ausgabetyp: Kein, Unbekannt
  • Vorauflage: 978-1-4129-9127-8
  • Nachauflage: 978-1-5063-9178-6

Autoren/Hrsg.

Autoren

Gau, Jacinta M.

Jacinta M. Gau, Ph.D., is an associate professor in the Department of Criminal Justice at the University of Central Florida. She received her doctorate from Washington State University in 2008. Her primary areas of research are policing and criminal justice policy, and she has a strong quantitative background. Dr. Gau’s work has appeared in journals such as Justice Quarterly, British Journal of Criminology, Criminal Justice and Behavior, Crime & Delinquency, Criminology & Public Policy, Police Quarterly, Policing: An International Journal of Police Strategies & Management, and the Journal of Criminal Justice Education. In addition to Statistics for Criminology and Criminal Justice, she is author of Criminal Justice Policy: Origins and Effectiveness (Oxford University Press) and co-author of Key Ideas in Criminology and Criminal Justice (SAGE Publications). Additionally, she co-edits Race and Justice: An International Journal, published by SAGE.

Preface to the Second Edition
Acknowledgments
About the Author
Part 1-Descriptive Statistics
Chapter 1-Introduction to the Use of Statistics in Criminal Justice and Criminology
Science: Basic Terms and Concepts
Types of Scientific Research in Criminal Justice and Criminology
Software Packages for Statistical Analysis
Organization of the Book
Chapter 1 Review Problems
Chapter 2-Types of Variables and Levels of Measurement
Units of Analysis
Independent and Dependent Variables
Relationships Between Variables: A Cautionary Note
Levels of Measurement
Chapter Summary
Chapter 2 Review Problems
Chapter 3-Organizing, Displaying, and Presenting Data
Data Distributions
Graphs and Charts
Grouped Data
SPSS
Chapter Summary
Chapter 3 Review Problems
Chapter 4-Measures of Central Tendency
The Mode
The Median
The Mean
Using the Mean and Median to Determine Distribution Shape
Deviation Scores and the Mean as the Midpoint of the Magnitudes
SPSS
Chapter Summary
Chapter 4 Review Problems
Chapter 5-Measures of Dispersion
The Variation Ratio
The Range
The Variance
The Standard Deviation
The Standard Deviation and the Normal Curve
SPSS
Chapter Summary
Chapter 5 Review Problems
Part 2-Probability and Distributions
Chapter 6-Probability
Discrete Probability: The Binomial Probability Distribution
Continuous Probability: The Standard Normal Curve
Chapter Summary
Chapter 6 Review Problems
Chapter 7-Population, Sample, and Sampling Distributions
Empirical Distributions: Population and Sample Distributions
Theoretical Distributions: Sampling Distributions
Sample Size and the Sampling Distribution: The z and t Distributions
Chapter Summary
Chapter 7 Review Problems
Chapter 8-Point Estimates and Confidence Intervals
The Level of Confidence: The Probability of Being Correct
Confidence Intervals for Means with Large Samples
Confidence Intervals for Means with Small Samples
Confidence Intervals With Proportions and Percentages
Chapter Summary
Chapter 8 Review Problems
Part 3-Hypothesis Testing
Chapter 9-Hypothesis Testing: A Conceptual Introduction
Sample Statistics and Population Parameters: Sampling Error or True Difference?
Null and Alternative Hypotheses
Chapter Summary
Chapter 9 Review Problems
Chapter 10-Hypothesis Testing With Two Categorical Variables: Chi-Square
Conceptual Basis of the Chi-Square Test: Statistical Dependence and Independence
The Chi-Square Test of Independence
Measures of Association
SPSS
Chapter Summary
Chapter 10 Review Problems
Chapter 11-Hypothesis Testing With Two Population Means or Proportions
Two-Population Tests for Differences Between Means: t Tests
Two-Population Tests for Differences Between Proportions
SPSS
Chapter Summary
Chapter 11 Review Problems
Chapter 12-Hypothesis Testing With Three or More Population Means: Analysis of Variance
ANOVA: Different Types of Variances
When the Null Is Rejected: A Measure of Association and Post Hoc Tests
SPSS
Chapter Summary
Chapter 12 Review Problems
Chapter 13-Hypothesis Testing With Two Continuous Variables: Correlation
Beyond Statistical Significance: Sign, Magnitude, and Coefficient of Determination
SPSS
Chapter Summary
Chapter 13 Review Problems
Chapter 14-Introduction to Regression Analysis
One Independent Variable and One Dependent Variable: Bivariate Regression
Adding More Independent Variables: Multiple Regression
Ordinary Least Squares Regression in SPSS
When the Dependent Variable Is Not Continuous and Normally Distributed: Alternatives to OLS
Chapter Summary
Chapter 14 Review Problems
Appendix A—Review of Basic Mathematical Techniques
Appendix B—The Standard Normal (z) Distribution
Appendix C—t Distribution
Appendix D—Chi-Square (?²) Distribution
Appendix E—F Distribution
Glossary
Answers to Learning Checks
Answers to Review Problems
References
Index