A well-known weakness of regression modeling based on observational data is that the observed association between two variables may be because both are related to a third variable that has been omitted from the regression model. This phenomenon is commonly referred to as “spurious correlation.” The term spurious correlation dates back to at least Pearson (1897).
Neyman (1952, pp. 143–154) provides an example based on fictitious data which dramatically illustrates spurious correlation. According to Kronmal (1993, p. 379), a fictitious friend of Neyman was interested in empirically examining the theory that storks bring babies and collected data on the number of women, babies born and storks in each of 50 counties. This fictitious data set was reported in Kronmal (1993, p. 383) and it can be found on the web page associated with Sheather (2009), namely, http://www.stat.tamu.edu/~sheather/book.
Figure 1shows scatter plots of all three variables from the stork data set along with the...
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References and Further Reading
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Kronmal RA (1993) Spurious correlation and the fallacy of the ratio standard revisited. J R Stat Soc A 156:379–392
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Sheather, S.J. (2011). Spurious Correlation. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_534
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