In Example 6, lack of consistency led to the suspicion that the data were phony. Too much precision or regularity can lead to the same suspicion, as when a student’s lab report contains data that are exactly as the theory predicts. The laboratory instructor knows that the accuracy of the equipment and the student’s laboratory technique are not good enough to give such perfect results. He suspects that the student made them up. Here is an example about fraud in medical research.
EXAMPLE 8 More fake data
As an up-and-coming radiologist at the University of California, San Diego, Robert Slutsky appeared to publish many articles. However, when a reviewer was asked to write a letter for Slutsky’s promotion, the reviewer discovered that two articles written by Slutsky had the exact same data, but with different numbers of subjects. Needless to say, Slutsky did not get a promotion—in fact, he resigned.
In this case, suspicious regularity (exact same data) combined with inconsistency (different numbers of subjects) led a careful reader to suspect fraud.