Essentials of statistics for criminology and criminal justice
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書誌事項
Essentials of statistics for criminology and criminal justice
SAGE, c2018
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
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 AnalysisChapter 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 MeanChapter 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 DeviationChapter 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 TheoremChapter 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 SampleChapter 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 SamplesChapter 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 VariablesChapter 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 SamplesChapter 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 ProbationChapter 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 rChapter 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 ViolenceAppendix A. Review of Basic Mathematical OperationsAppendix B. Statistical TablesAppendix C. Solutions for Odd-Numbered Practice ProblemsAppendix D. SPSS Exercises
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