[IPAC-List] Amer Stat Assn Statement on p values issued 3/2016

[Joel Wiesen]

In case you missed it:
http://www.amstat.org/asa/files/pdfs/P-ValueStatement.pdf

"The statement’s six principles, many of which address misconceptions 
and misuse of the p-value, are the following:

1. P-values can indicate how incompatible the data are
  with a specified statistical model.

2. P-values do not measure the probability that the studied hypothesis 
is true, or the probability that the data were produced by random chance 
alone.

3. Scientific conclusions and business or policy decisions should not be 
based only on whether a p-value passes a specific threshold.

4. Proper inference requires full reporting and transparency.

5. A p-value, or statistical significance, does not measure the size of 
an effect or the importance of a result.

6. By itself, a p-value does not provide a good measure of evidence 
regarding a model or hypothesis.

The statement has short paragraphs elaborating on each principle."



-- 
Joel P. Wiesen, Ph.D., Director
Applied Personnel Research
62 Candlewood Road
Scarsdale, NY 10583-6040
http://www.linkedin.com/in/joelwiesen
(617) 244-8859
http://appliedpersonnelresearch.com




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