What looks like a link between two things, when the “link” is really caused by a third thing. For example, doctors often own houses, but that is not just because doctors are doctors; it is also because doctors earn a lot of money.

Observed association between two variables that could be attributed to a common, but unmeasured third variable. The adjective “spurious” correctly refers to the inference made from the correlation, not the correlation itself. EX: If A and B are correlated, it is not possible to conclude that (on that fact alone) that A causes B. It is also possible that B causes A or that a C exists that influences both A and B in a systematic fashion. [See correlation coefficient, partial 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

The strength and direction of an association between an independent and dependent variable depends on the value of a third variable.

In statistics a correlation between data that exists because of a statistical fluke (rather than true correlation (not to be confused with causality as correlation does not prove causality which can exist between the two correlated factors or be stemming from one or more unknown factors affecting the two being analyzed)), it is called a spurious correlation. One of the measures of goodness of fit is the R2 statistic. Spurious correlation occurs when the sample size is small, and the R2 metric is misleading i.e. there is a high likelihood that the fit occurred purely by chance.