Paradoxes in economics tend to be the veridical type, typically counterintuitive outcomes of economic theory, such as Simpson's paradox.

While weighted means generally behave in a similar fashion to arithmetic means, they do have a few counterintuitive properties, as captured for instance in Simpson's paradox.

Simpson's paradox for continuous data: a positive trend appears for two separate groups ( blue and red ), a negative trend ( black, dashed ) appears when the data are combined.

In probability and statistics, Simpson's paradox ( or the Yule – Simpson effect ) is a paradox in which a correlation present in different groups is reversed when the groups are combined.

Many statisticians believe that the mainstream public should be informed of the counter-intuitive results in statistics such as Simpson's paradox.

The name Simpson's paradox was introduced by Colin R. Blyth in 1972.

Since Edward Simpson did not actually discover this statistical paradox, some writers, instead, have used the impersonal names reversal paradox and amalgamation paradox in referring to what is now called Simpson's Paradox and the Yule-Simpson effect.

Critics of the movement, however, point to various discrepancies that result from current state standardized testing practices, including problems with test validity and reliability and false correlations ( see Simpson's paradox ).

The same is true of children born to poor parents, and of children born at high altitude ; these are all examples of Simpson's paradox.

* Simpson's paradox, of which the Low birth weight paradox is an example

* Simpson's paradox

* Simpson's paradox

* Yule – Simpson effect ( a. k. a. Simpson's paradox ) – Edward H. Simpson and Udny Yule

( 1999 ) also criticised Van Howe's paper, stating that his results were a case of " Simpson's paradox, which is a type of confounding that can occur in epidemiological analyses when data from different strata with widely divergent exposure levels are combined, resulting in a combined measure of association that is not consistent with the results for each of the individual strata.

The failure of the consistency criterion can be seen as an example of Simpson's paradox.

Though it is mostly unknown to laypeople, Simpson's Paradox is well known to statisticians, and it is described in a few introductory statistics books.

Berkson's paradox or Berkson's fallacy is a result in conditional probability and statistics which is counterintuitive for some people, and hence a veridical paradox.

The concept is sometimes referred to as the Solow computer paradox in reference to Robert Solow's 1987 quip, " You can see the computer age everywhere but in the productivity statistics.

* In 2005 Kwok & Yu used an updated methodology to argue for a lower or zero paradox in US trade statistics, though the paradox is still derived in other developed nations.