Changing the traditional paradigms of hypothesis testing and statistical significance,   Luis Pericchi,   UPR Río Piedras,  Wed, 4 April, 2012,   10:00 a.m. A-211


Quoting from :

Siegfried, T. (2010) Odds Are, It's Wrong Science fails to face the shortcomings of statistics. ScienceNews, March 27th, 2010; Vol.177 #7 (p. 26)

"It’s science’s dirtiest secret: The “scientific method” of testing hypotheses by statistical analysis stands on a flimsy foundation. Statistical tests are supposed to guide scientists in judging whether an experimental result reflects some real effect or is merely a random fluke, but the standard methods mix mutually inconsistent philosophies and offer no meaningful basis for making such decisions. Even when performed correctly, statistical tests are widely misunderstood and frequently misinterpreted. As a result, countless conclusions in the scientific literature are erroneous, and tests of medical dangers or treatments are often contradictory and confusing."

In this talk I will present what Pereira and myself recently read in an international meeting in Brasil: How to explain the shortcomings of the traditional method of scientific testing and how to improve it.