Both the terms correlation and causation are often used when interpreting, evaluating, and describing statistical data. While correlations and causations can be associated, they do not need to be related or linked. A correlation and a causation are two distinct and separate statistical terms that can each individually be used to describe and interpret different types of data. Sometimes the two terms are mistakenly used interchangeably, which could misrepresent important trends in a given data set. The danger of using these terms as synonyms has become even more problematic in recent years with the continued emergence of research projects reliving on big data. Any time a researcher utilizes a large dataset with thousands of observations, they are bound to find correlations between variables; however, with such large datasets, there is an inherent risk that these correlations are spurious opposed to causal.
A correlation, sometimes called an association, describes the linear relationship...
Further Readings
Correlation Coefficients. (2005, January 1). Retrieved 14 Aug 2014, from http://www.andrews.edu/~calkins/math/edrm611/edrm05.htm.
Green, N. (2012, January 6). Correlation is not causation. Retrieved 14 Aug 2014, from http://www.theguardian.com/science/blog/2012/jan/06/correlation-causation.
Jaffe, A. (2010, January 1). Correlation, causation, and association – What does it all mean? Retrieved 14 Aug 2014, from http://www.psychologytoday.com/blog/all-about-addiction/201003/correlation-causation-and-association-what-does-it-all-mean.
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Anderson, B., Geras, M. (2018). Correlation Versus Causation. In: Schintler, L., McNeely, C. (eds) Encyclopedia of Big Data. Springer, Cham. https://doi.org/10.1007/978-3-319-32001-4_45-1
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DOI: https://doi.org/10.1007/978-3-319-32001-4_45-1
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