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A Beginner's Guide to Statistics for Criminology and Criminal Justice Using R

A Beginner's Guide to Statistics for Criminology and Criminal Justice Using R

  • 作者:
  • 出版商: Springer-Verlag
  • ISBN: 9783030506278
  • 出版时间 June 2022
  • 规格: Paperback
  • 适应领域: Switzerland ? 免责申明:
    Countri(es) stated herein are used as reference only
JP¥13,742.80
发货时间:大约 4-5 weeks
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  • 描述 
  • 大纲 
  • 详细

    This book provides hands-on guidance for researchers and practitioners in criminal justice and criminology to perform statistical analyses and data visualization in the free and open-source software R. It offers a step-by-step guide for beginners to become familiar with the RStudio platform and tidyverse set of packages.

    This volume will help users master the fundamentals of the R programming language, providing tutorials in each chapter that lay out research questions and hypotheses centering around a real criminal justice dataset, such as data from the National Survey on Drug Use and Health, National Crime Victimization Survey, Youth Risk Behavior Surveillance System, The Monitoring the Future Study, and The National Youth Survey. Users will also learn how to manipulate common sources of agency data, such as calls-for-service (CFS) data. The end of each chapter includes exercises that reinforce the R tutorial examples, designed to help master the software as well as to provide practice on statistical concepts, data analysis, and interpretation of results.

    The text can be used as a stand-alone guide to learning R or it can be used as a companion guide to an introductory statistics textbook, such as Basic Statistics in Criminal Justice (2020).

  • 1. Getting started
    2. Managing your data
    3. Data visualization
    4. Spatiotemporal data visualization and basic crime analysis
    5. Descriptive statistics: measures of central tendency
    6. Descriptive statistics: measures of dispersion
    7. Statistical inference in criminal justice research
    8. Defining the observed significance level of a test
    9. Hypothesis testing using the binomial distribution
    10. Chi-square: a test commonly used for nominal-level measures
    11. The normal distribution and its application to tests of statistical significance
    12. Comparing means in two samples
    13. Analysis of variance
    14. Measures of association for nominal and ordinal variables
    15. Measuring association for interval data
    16. Introduction to regression analysis

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