Association, Cause, and Correlation

  • Stephen P. GlasserEmail author
  • Gary Cutter


Anything one measures can become data, but only those data that have meaning can become information. Information is almost always useful; data may or may not be. This chapter will address the various ways one can measure the degree of association between an exposure and an outcome and will include a discussion of relative and absolute risk, odds ratios, number needed to treat, and related measures. In addition, this chapter will introduce the concept of causal inference.


Probability Chi-square test Relative risk Attributable risk Relative risk reduction Number needed to treat Correlation Regression Causation 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Division of Preventive MedicineUniversity of Alabama at BirminghamBirminghamUSA
  2. 2.School of Public HealthUniversity of Alabama at BirminghamBirminghamUSA

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