Archive for March, 2016

American Statistical Association (ASA) defends itself against P-shooters

With the fundamental statistic of P value coming under severe attack, e.g., it being banned in early 2015 by the Basic and Applied Social Psychology (BASP) journal, the ASA has been compelled to issue an unprecedented press release with guidelines for avoiding misuse of hypothesis testing by scientists claiming significant experimental results.*  “The ASA statement is intended to steer research into a ‘post p<0.05 era,’” said Ron Wasserstein, the ASA’s executive director.

“To pounce on tiny P values and ignore the larger question is to fall prey to the ‘seductive certainty of significance.’”

– Geoff Cumming, emeritus psychologist, La Trobe University, Melbourne, Australia

The ASA statement on “Statistical Significance and P-Values” can be seen here.  It includes 6 guidelines on proper use of this essential tool for assessing research data, beginning with the assertion that “P-values can indicate how incompatible the data are with a specified statistical model.”

*See, for example, this Nature article that claims P values, the ‘gold standard’ of statistical validity, are not as reliable as many scientists assume.

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Big data puts an end to the reign of statistics

Michael S. Malone of the Wall Street Journal proclaimed last month* that

One of the most extraordinary features of big data is that it signals the end of the reign of statistics.  For 400 years, we’ve been forced to sample complex systems and extrapolate.  Now, with big data, it is possible to measure everything…

Based on what I’ve gathered (admittedly only a small and probably unrepresentative sample), I think this is very unlikely.  Nonetheless, if I were a statistician, I would reposition myself as a “Big Data Scientist”.

*”The Big-Data Future Has Arrived”, 2/22/16.

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