Freedman's Paradox

An interesting definition:

"In situations where limited knowledge of a system exists and the ratio of data points to variables is small, variable selection methods can often be misleading. Freedman (Am Stat 37:152-155, 1983) demonstrated how common it is to select completely unrelated variables as highly 'significant' when the number of data points is similar in magnitude to the number of variables." 

Lukacs, Burnham, and Anderson (2010).

References

Freedman, D. A. (1983). A Note on Screening Regression Equations. The American Statistician, 37(2), 152-155.