spurious correlation

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Noun1.spurious correlation - a correlation between two variables (e.g., between the number of electric motors in the home and grades at school) that does not result from any direct relation between them (buying electric motors will not raise grades) but from their relation to other variables
statistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters
correlational statistics, correlation - a statistical relation between two or more variables such that systematic changes in the value of one variable are accompanied by systematic changes in the other
References in periodicals archive ?
Marmol (1998) suggested that spurious correlation generally occurs in regressions including fractionally integrated processes.
The author uses several equations and reduces the number of parameters to obtain t-values that are at least free of spurious correlation, but suffer from multicollinearity, because of the many interrelated variables used (ten in the original formulation).
In recent research I show that the correlation between carbon emissions and global temperature is yet another example of spurious correlation.
Of course, I draw no such conclusion, as I recognise that such spurious correlation is both alarmist and dangerous.
His results suggest that the spatial correlation between teachers' residences, students' residences, and schools could lead to spurious correlation between student attributes and teacher characteristics.
finding appears to be a clear example of a spurious correlation (otherwise known as illusory correlation or the "lurking variable"), a situation in which two otherwise unrelated variables are correlated because each is related to a third unmeasured variable.
An observed association between marijuana use and labor market outcomes may be causal, or it may merely reflect a spurious correlation due to unobserved individual-level factors that affect both marijuana use and labor market outcomes.