Data manipulation

Data manipulation is the presentation of scientific data in a misleading way to support a hypothesis which is actually without merit. Informally called "fudging the data", this practice includes selective reporting (see also publication bias) and even simply making up false data.

Examples of selective reporting abound. The easiest and most common examples involve choosing a group of results which follow a pattern consistent with the preferred hypothesis - while ignoring other results or "data runs" which contradict the hypothesis.

Michael Fumento writers:


 * Consider a report by three environmentalist authors back in 1988 in Journal of the American Medical Association (JAMA), analyzing male-female birth ratios between 1970 and 1990. The authors found male births declining, and predictably blamed man-made chemicals. Yet public data going back to 1940 showed gender ratios are always changing, for no obvious reason. Years that disproved their thesis were simply sliced out.

Psychic researchers have long disputed over studies showing people with ESP ability. Critics accuse ESP proponents of only publishing experiments with positive results and shelving those which show negative results. A "positive result" is a test run (or data run) in which the subject guesses a hidden card, etc., at a much higher frequency than random chance.

The deception involved in both cases is that the hypothesis is not confirmed by the totality of the experiments - only by a tiny, selected group of "successful" tests.

Scientists in general question the validity of study results which cannot be reproduced by other investigators. However, some scientists refuse to publish their data and methods.