Statistics for criminology and criminal justice
著者
書誌事項
Statistics for criminology and criminal justice
SAGE, c2022
5th ed
- : pbk
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注記
"SAGE college publishing"--Back cover
Includes bibliographical references (p. 578-581) and index
内容説明・目次
内容説明
Communicating the excitement and importance of criminal justice research, this practical and comprehensive book shows students how to perform and understand statistical analyses, while helping them recognize the connection between statistical analyses used in everyday life and their importance to criminology and criminal justice. This updated Fifth Edition is packed with real-world case studies and contemporary examples utilizing the most current crime data and empirical research available. Each chapter presents a particular statistical method in the context of a substantive research story.
目次
Chapter 1. The Importance of Statistics in the Criminological Sciences or Why Do I have to Learn This Stuff?
PART I. Univariate Analysis: Describing Variable Distributions
Chapter 2. Levels of Measurement and Aggregation
Chapter 3. Understanding Data Distributions: Tabular and Graphical Techniques
Chapter 4. Measures of Central Tendency
Chapter 5. Measures of Dispersion
PART II. Making Inferences in Univariate Analysis: Generalizing From a Sample to the Population
Chapter 6. Probability, Probability Distributions, and an Introduction to Inferential Testing
Chapter 7. Point Estimation and Confidence Intervals
Chapter 8. From Estimation to Statistical Tests: Hypothesis Testing for One Population Mean and Proportion
PART III. Bivariate Analysis: Relationships Between Two Variables
Chapter 9. Testing Hypotheses With Categorical Data
Chapter 10. Hypothesis Tests Involving Two Population Means or Proportions
Chapter 11. Hypothesis Tests Involving Three or More Population Means: Analysis of Variance
Chapter 12. Bivariate Correlation and Regression
PART IV. Multivariable Analysis: Predicting One Dependent Variable with Two or More Independent Variables
Chapter 13. Controlling for a Third Variable: Multiple OLS Regression
Chapter 14. Regression Analysis With a Dichotomous Dependent Variable: Logit Models
「Nielsen BookData」 より
