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Measuring Association for Interval-Level Data: Pearson’s Correlation Coefficient

  • David Weisburd
  • Chester Britt
Chapter

Abstract

This chapter introduces the linear correlation coefficient, a widely used descriptive statistic that enables the researcher to describe the relationship between two interval-level measures. This situation is encountered often in criminal justice research. For example, researchers may want to establish whether number of prior arrests is related to age, education, or monthly income. similarly, it is common in criminal justice research to ask whether the severity of a sanction measured on an interval scale (e.g., number of years sentenced to imprisonment or amount of a fine) is related to such variables as the amount stolen in an offense or the number of prior arrests or convictions of a defendant. We also examine an alternative rank-order measure of association that may be used when the linear correlation coefficient will lead to misleading results.

Keywords

Unemployment Rate Population Distribution Misleading Result Interval Scale Young Offender 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • David Weisburd
    • 1
    • 2
  • Chester Britt
    • 3
  1. 1.Faculty of Law Institute of CriminologyHebrew University of JerusalemJerusalemIsrael
  2. 2.Department of Criminology, Law and SocietyGeorge Mason UniversityFairfaxUSA
  3. 3.School of Criminology and Criminal JusticeNortheastern UniversityBostonUSA

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