Statistics for Criminology and Criminal Justice

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 Third EditionAcknowledgmentsAbout the AuthorPart I: Descriptive StatisticsChapter 1: Introduction to the Use of Statistics in Criminal Justice and CriminologyScience: Basic Terms and ConceptsTypes of Scientific Research in Criminal Justice and CriminologySoftware Packages for Statistical AnalysisOrganization of the BookThinking CriticallyReview ProblemsKey TermsChapter 2: Types of Variables and Levels of MeasurementUnits and Levels of AnalysisIndependent Variables and Dependent VariablesCorrelation versus CausationLevels of MeasurementChapter SummaryThinking CriticallyReview ProblemsKey TermsChapter 3: Organizing, Displaying, and Presenting DataData DistributionsGraphs and ChartsGrouping DataSPSSChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterChapter 4: Measures of Central TendencyDistribution ShapesThe MedianThe MeanUsing Means and Medians to Determine Distribution ShapeDeviation Scores and the Mean as the Midpoint of the MagnitudesSPSSChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterChapter 5: Measures of DispersionThe Variation RatioThe RangeThe VarianceThe Standard DeviationThe Standard Deviation and the Normal CurveChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterPart II: Probability and DistributionsChapter 6: ProbabilityDiscrete Probability: The Binomial Probability DistributionContinuous Probability: The Standard Normal CurveChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterChapter 7: Population, Sample, and Sampling DistributionsEmpirical Distributions: Population and Sample DistributionsTheoretical Distributions: Sampling DistributionsSample Size and the Sampling Distribution: The z and t DistributionsChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterChapter 8: Point Estimates and Confidence IntervalsThe Level of Confidence: The Probability of Being CorrectConfidence Intervals for Means with Large SamplesConfidence Intervals for Means with Small SamplesConfidence Intervals with ProportionsChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterPart III: Hypothesis TestingChapter 9: Hypothesis Testing: A Conceptual IntroductionSample Statistics and Population Parameters: Sampling Error or True Difference?Null and Alternative HypothesesChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterChapter 10: Hypothesis Testing with Two Categorical Variables: Chi-SquareThe Chi-Square Test of IndependenceMeasures of AssociationSPSSChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterChapter 11: Hypothesis Testing with Two Population Means or ProportionsTwo-Population Tests for Differences Between Means: t TestsTwo-Population Tests for Differences Between ProportionsSPSSChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterChapter 12: Hypothesis Testing with Three or More Population Means: Analysis of VarianceANOVA: Different Types of VariancesWhen the Null Is Rejected: A Measure of Association and Post Hoc TestsSPSSChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterChapter 13: Hypothesis Testing with Two Continuous Variables: CorrelationBeyond Statistical Significance: Sign, Magnitude, and Coefficient of DeterminationSPSSChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterChapter 14: Introduction to Regression AnalysisOne Independent Variable and One Dependent Variable: Bivariate RegressionAdding Independent Variables: Multiple RegressionAlternatives to Ordinary Least Squares RegressionOrdinary Least Squares and Logistic Regression in SPSSChapter SummaryThinking CriticallyReview ProblemsKey TermsGlossary of Symbols and Abbreviations Introduced in This ChapterAppendix A. Review of Basic Mathematical TechniquesAppendix B. Standard Normal (z) DistributionAppendix C. t DistributionAppendix D. Chi-Square (?2) DistributionAppendix E. F DistributionGlossaryLearning Checks Answer KeyReview Problems Answer KeyReferencesIndex