10 Correlations That Are Not Causations

Hormonal Imbalance
The story of hormone replacement therapy, once widely used to treat symptoms of menopause, turned out not to be so straightforward after all. Christopher Pattbery/iStock/Thinkstock

Randomized controlled trials are the gold standard in statistics, but sometimes -- in epidemiology, for example -- ethical and practical considerations force researchers to analyze available cases. Unfortunately, such observational studies risk bias, hidden variables and, worst of all, a study group that might not reflect the population as a whole. Studying a representative sample is vital; it allows researchers to apply results to people outside of the study, like the rest of us.

A case in point: hormone replacement therapy (HRT). Beyond treating symptoms associated with menopause, it was once hailed for potentially reducing coronary heart disease (CHD) risk, thanks to a much-ballyhooed 1991 observational study [source: Stampfer and Colditz]. But later randomized controlled studies, including the large-scale Women's Health Initiative, revealed either a negative relationship, or a statistically insignificant one, between HRT and CHD [sources: Lawlor et al.; New York Times].

Why the difference? For one thing, women who use HRT tend to come from higher socioeconomic strata and receive better quality of diet and exercise – a hidden explanatory relationship for which the observational study failed to fully account [source: Lawlor et al.].