Follow-up to the statement on p-values by ASA

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The American Statistical Association Says [Mostly] No to p-values

Norman Matloff has published a new post after receiving criticism and comments about stating “The ASA says No to p-values” in his post I wrote about some days ago. He defends his interpretation in this new post. However, I think, the interpretation of  the statement in a context different from the “Big data” field to which he is used to does not need to always be “Says No to p-values” but instead in many cases could be “Use p-values to assess the strength of the evidence and nothing else”.  However, “tests” with binary outcomes on probabilities that are essentially continuous, will always be based on an arbitrary threshold and discard a great deal of information. Consequently to me using as suggested by Norman Matloff  “assess” in place of “test” makes a lot of sense.

The new post is at

“Itʹs Not The P-valuesʹ Fault”

Joint post by Yoav Benjamini and Tal Galili. The post highlights points raised by Yoav in his official response to the ASA statement…

Source: It’s Not The P-values’ Fault – Reflections On The Recent ASA Statement (+relevant R Resources) | R-statistics Blog

P-values: the Continuing Saga

I highly recommend the blog post by Yoav Benjamini and Tal Galili in defense of (carefully used) p-values. I disagree with much of it, but the exposition is very clear, and there is a nice guide to…

Source: P-values: the Continuing Saga | Mad (Data) Scientist

The argument continues with this response from Norman Matloff.

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