Odds Are, It’s Wrong

There is something very ‘taoist’ in the title, “Odds Are, It’s Wrong“, an article in Science News. Right off the bat it reminds me of, ‘Not to know yet to think that one knows will lead to difficulty’. The patient search for truth pales next to our hunger for ‘the answer’. Science is humanity’s best attempt to balance the two, but often fails, as this article points out. This is especially true for the ’softer’ sciences, e.g., social, physiological, medical. The eye-opening information here helps remind us that we are animals first, and whatever else we think or wish we were a distant second.

The following quotes, from experts in the field and absent in the online version, show there is push back. Although, like getting government to keep a balanced budget, there cries for cautious will go unheeded, until some awful visitation descends upon them.

“Despite the awesome pre-eminence this method has attained … it is based upon a fundamental misunderstanding of the nature of rational inference, and is seldom if ever appropriate to the aims of scientific research.” —William Rozeboom, 1960

“Huge sums of money are spent annually on research that is seriously flawed through the use of inappropri­ate designs, unrepresentative samples, small samples, incorrect methods of analysis, and faulty interpretation.” - D.G.Altman, 1994

“Many investigators do not know what our most cherished, and ubiquitous, research desideratum—’statistical significance’—really means. This … signals an educational failure of the first order.” - Raymond Hubbard and J. Scott Armstrong, 2006

“These classical methods [of significance testing] are in fact intellectually quite indefensible and do not deserve their social success.”- Colin Howson and Peter Urbach, 2006

“A finding of ’statistical’ significance … is on its own almost valueless, a meaning-less parlor game.^{“ –} Stephen Ziliak and Deirdre McCloskey, 2008

“The methods of statistical inference in current use … have contributed to a widespread misperception … that statistical methods can provide a num‑ber that by itself reflects a probability of reaching erroneous conclusions. This belief has damaged the quality of scientific reasoning and discourse.”  – Steven Goodman, 1999

“What used to be called judgment is now called prejudice, and what used to be called prejudice is now called a null hypoth-esis…. It is dangerous nonsense.” – A, W F. Edwards, 1972