[cpdiii]

“Recently, p-values have been criticized and even banned by some journals, because they are used by researchers, who cherry-pick observations and repeat experiments until they obtain a p-value worth publishing to obtain grant money, get tenure, or for political reasons”

There is nothing wrong with P Values. If you cherry pick the data all the results are crap. It is no longer valid data.

[LambSlave]

There is nothing wrong with P Values. If you cherry pick the data all the results are crap. It is no longer valid data.

You don't need to cherry pick; 100 researchers do the same experiment (does drug A cause weight loss). 98 of them find no effect, which is not a publication worthy result, so they don't get published, but the two who do find an effect (say p 0.03, 0.04) publish their results and now we have a problem.

[DoodleBob]

In some sense, p-values are a relic from old times, when computing power was limited and mathematical / theoretical formulas were favored and easier to deal with than lengthy computations.

And THAT, is where the writer surrenders his position.

As stated, correctly, there is nothing wrong with p-values...just like there is nothing wrong with guns. It is when p-values are put in the hands of unscrupulous people with the intent to do harm, that bad things can happen. Furthermore, models that have other problems like multicollinearity, can lead to inefficient parameter estimates and problematic p-values.

However, this is all Stat 101 stuff. The REAL intent behind this article, is to subtly paint statistics in a bad light and puff up the data science/machine learning professionals. Which is sad, since Dr. Granville has good credentials.