So Science Gets it Wrong. Then What?
It’s hard to think of a scientist whose reputation is more squeaky-clean than the shy Austrian monk Gregor Mendel. His story invariably begins in the abbey garden, where from 1856 to 1863 he bred thousands of pea plants and painstakingly counted how traits pass from one generation to the next.
His data showed that many features are inherited in predictable ratios: dominant traits, like round seeds, are passed to three out of four daughter plants, whereas recessive ones, like wrinkled seeds, go to just one in four. Mendel discovered how genes work before anybody knew that they existed.
The ideas behind Mendel’s experiments are sound, but according to an infamous statistical analysis, the good friar fudged data to fit his pre-existing notions. In 1936, R.A. Fisher of University College London argued that Mendel’s tallies of traits — claiming, for instance, that 5,474 daughter seeds were round and 1,850 wrinkled — were too spot-on for the expected 3:1 ratio to be true. “The data of most, if not all, of the experiments have been falsified so as to agree closely with Mendel’s expectations,” Fisher wrote. In other words: Mendel was either presenting a choice subset of his data, or cooking the books outright.
A few years ago, statisticians in Portugal re-analyzed Mendel’s data and Fisher’s calculations, and suggested that Mendel was guilty of an unconscious and systematic bias, rather than fraud*. Whether Mendel cheated or not, there’s no question that fudges and mistakes and transgressions happen in science. So, fellow science-lovers, should we be worried about this?
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