  The primary objective of this paper is to revisit Simpson's paradox using a
statistical misspecification perspective. It is argued that the reversal of
statistical associations is sometimes spurious, stemming from invalid
probabilistic assumptions imposed on the data. The concept of statistical
misspecification is used to formalize the vague term `spurious results' as
`statistically untrustworthy' inference results. This perspective sheds new
light on the paradox by distingusing between statistically trustworthy vs.
untrustworthy association reversals. It turns out that in both cases there is
nothing counterintuitive to explain or account for. This perspective is also
used to revisit the causal `resolution' of the paradox in an attempt to
delineate the modeling and inference issues raised by the statistical
misspecification perspective. The main arguments are illustrated using both
actual and hypothetical data from the literature, including Yule's
"nonsense-correlations" and the Berkeley admissions study.
