Paternoster / Bachman Essentials of Statistics for Criminology and Criminal Justice

1. Auflage 2017
ISBN: 978-1-5063-7713-1
Verlag: SAGE Publications
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 424 Seiten, EPUB

Essentials of Statistics for Criminology and Criminal Justice helps students understand the vital role that research and statistics play in the study of criminology and criminal justice by showing them how to conduct and interpret statistics in real-world settings with a step-by-step approach to solving problems. This practical, applied approach offers students the fundamentals of descriptive and inferential statistics in a concise and easy-to-understand format—avoiding complicated proofs and discussions of statistical theory. The examples and case studies provide relevant examples for criminology and criminal justice students, and deal with contemporary issues related to crime, corrections, police, and the judicial system. Students will not only learn about the "how to" in statistics, but they will also recognize its importance in today’s criminal justice system.

Autoren/Hrsg.

Paternoster, Raymond

Bachman, Ronet D.

Inhaltsverzeichnis

Chapter 1. Setting the Stage: Why Learning This Stuff is Important!

Setting the Stage for Statistical Inquiry

The Role of Statistical Methods in Criminology and Criminal Justice

Populations and Samples

Descriptive and Inferential Statistics

Levels of Measurement

Ways of Presenting Variable

Units of Analysis

Chapter 2. Understanding Data Distributions With Tables and Graphs

The Tabular and Graphical Display of Qualitative Data

The Tabular and Graphical Display of Quantitative Data

The Shape of a Distribution

Time Plots

Chapter 3. Measures of Central Tendency

The Mode

The Median

The Mean

Chapter 4. Measures of Dispersion

Measuring Dispersion for Nominal- and Ordinal-Level Variables

Measuring Dispersion for Internal- and Ratio-Level Variables

The Standard Deviation and Variance

Computational Formulas for Variance and Standard Deviation

Chapter 5. Moving Beyond Description: Introducing Inferential Statistics: Probability Distributions and an Introduction to Hypothesis Testing

Probability. What Is It Good for? Absolutely Everything!

The Rules of Probability

Probability Distributions

Samples, Populations, Sampling Distributions, and the Central Limit Theorem

Chapter 6. Point Estimation and Confidence Intervals

Making Inferences from Point Estimates: Confidence Intervals

Estimating a Population Mean From Large Samples

Estimating Confidence Intervals for a Mean From Small Samples

Estimating Confidence Intervals for Proportions and Percents With a Large Sample

Chapter 7. Hypothesis Testing for One Population Mean and Proportion

Hypothesis Testing for Population Means Using A Large Sample: The Z Test

Directional and Non-directional Hypothesis Tests

Hypothesis Testing for Population Means Using Small Samples: The t Test

Hypothesis Testing for Population Proportions and Percents Using Large Samples

Chapter 8.Testing Hypotheses With Two Categorical Variables

Contingency Tables and the Two Variable Chi-Square Test of Independence

The Chi-Square Test of Independence

A Simple-to-Use Computational Formula for the Chi-Square Test of Independence

Measures of Association: Determining the Strength of the Relationship Between Two Categorical Variables

Chapter 9. Hypothesis Tests Involving Two Population Means or Proportions

Explaining the Difference Between Two Sample Means

Sampling Distribution of Mean Differences

Testing a Hypothesis About the Difference Between Two Means: Independent Samples

Matched-Groups or Dependent-Samples t Test

Hypothesis Tests for the Difference Between Two Proportions: Large Samples

Chapter 10. Hypothesis Testing Involving Three or More Population Means: Analysis of Variance

The Logic of Analysis of Variance

Types of Variance: Total, Between-Groups, and Within-Group

Conducting a Hypothesis Test With ANOVA

After the F Test: Testing the Difference Between Pairs of Means

A Measure of Association Test With ANOVA

A Second ANOVA Example: Caseload Size and Success on Probation

Chapter 11. Bivariate Correlation and Ordinary Least Squares (OLS) Regression

Graphing the Bivariate Distribution Between Two Quantitative Variables: Scatterplots

The Pearson Correlation Coefficient

A More Precise Way to Interpret a Correlation: The Coefficient of Determination

The Least-Squares Regression Line and the Slope Coefficient

Comparison of b and r

Testing for the Significance of b and r

Chapter 12. Controlling for a Third Variable: Multiple OLS Regression

What Do We Mean by Controlling for Other Important Variables?

The Multiple Regression Equation

Comparing the Strength of a Relationship Using Beta Weights

Partial Correlation Coefficients

Hypothesis Testing in Multiple Regression

Another Example: Prison Density, Mean Age, and Rate of Inmate Violence

Appendix A. Review of Basic Mathematical Operations

Appendix B. Statistical Tables

Appendix C. Solutions for Odd-Numbered Practice Problems

Appendix D. SPSS Exercises

Über Autor(innen)

Bachman, Ronet D.

Ronet D. Bachman, PhD, worked as a statistician at the Bureau of Justice Statistics, U.S.

Department of Justice, before going back to an academic career; she is now a professor in the

Department of Sociology and Criminal Justice at the University of Delaware. She is coauthor

of Statistical Methods for Criminology and Criminal Justice and coeditor of Explaining Criminals

and Crime: Essays in Contemporary Criminal Theory. In addition, she is the author of Death and

Violence on the Reservation and coauthor of Stress, Culture, and Aggression; Murder American

Style; and Violence: The Enduring Problem, along with numerous articles and papers that examine

the epidemiology and etiology of violence, with particular emphasis on women, the elderly,

and minority populations as well as research examining desistance from crime. Her most recent

federally funded research was a mixed-methods study that examined the long-term desistance

trajectories of criminal justice involved drug-involved individuals who have been followed with

both quantitative and interview data for nearly thirty years. Her current state-funded research is

assessing the needs of violent crime victims, especially those whose voices are rarely heard such

as loved ones of homicide victims.

 

Paternoster, Raymond

Raymond Paternoster, Ph.D., is a professor in the Department of Criminology and Criminal Justice at the University of Maryland. He received his B.A. in sociology at the University of Delaware where he was introduced to criminology by Frank Scarpitti and obtained his Ph.D. at Florida State University under the careful and dedicated tutelage of Gordon Waldo and Ted Chiricos. He is coauthor of The Death Penalty: America’s Experience with Capital Punishment. In addition to his interest in statistics, he also pursues questions related to offender decision making and rational choice theory, desistance from crime, and capital punishment. With funding from the National Institute of Justice (NIJ), he is currently working on research comparing the decision-making patterns and characteristics of a sample of serious adult offenders and a comparable group of community members.