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A few years ago I had the privilege of working within an organization largely funded by the National Institutes of Health, supporting scientists on the leading edge of research into cellular senescence and other age-related phenomenon. I learned a great deal about a wide range of subjects and I also learned that science, even when conducted by well-meaning and highly qualified researchers, can result in garbage outputs. The two great journals Science and Nature both conclude the same thing a little while later, noting that at least 50% of all papers published in reputable journals aren’t worth the paper they’re printed on.
This is largely because too many scientists aren’t taught during their years of study how to design experiments. They don’t think like engineers and they don’t have the skills of professional statisticians and so their study designs are flawed and their data interpretations are often wildly wrong. Thus we get junk science.
This could be remedied, of course. PhD courses could include in-depth study of the differences between good and bad experimental design. PhD courses could include in-depth study of statistics so that researchers (a) understood the techniques properly, and (b) understood when to apply which technique to what type of dataset so as to produce valid results. Sadly, there’s little sign of this happening as the typical PhD student increasingly knows more and more about less and less; this is an inevitable consequence of having to prepare a thesis on a new and unique topic in order to obtain that much-needed…