How Statistics Can Help Minimize Scientific Retractions

The ability to duplicate an experiment and its results is a central tenet of the scientific method, but recent research has shown an alarming number of peer-reviewed papers are irreproducible.

A team of math and statistics professors has proposed a way to address one root of that problem by teaching reproducibility to aspiring scientists, using software that makes the concept feel logical rather than cumbersome.

Researchers from Smith College, Duke University and Amherst College looked at how introductory statistics students responded to a curriculum modified to stress reproducibility. Their work is detailed in a paper published Feb. 25 in the journal Technological Innovations in Statistics Education.

In 2013, on the heels of several retraction scandals and studies showing reproducibility rates as low as 10 percent for peer-reviewed articles, the prominent scientific journal Nature dedicated a special issue to the concerns over irreproducibility.

Nature’s editors announced measures to address the problem in its own pages, and encouraged the science community and funders to direct their attention to better training of young scientists.

“Too few biologists receive adequate training in statistics and other quantitative aspects of their subject,” the editors wrote. “Mentoring of young scientists on matters of rigour and transparency is inconsistent at best.”

The authors of the present study thus looked to their own classrooms for ways to incorporate the idea of reproducibility.

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