Thanks for the link. However, please note that much of the article does not make as strong a claim as the title of the article suggests.

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]]>Darn, Keith, that is cold.

]]>I’m impressed – that’s fast! Even given the starting point.

BTW, it reminded me of “Hiawatha Designs an Experiment”, a classic:

http://www-history.mcs.st-andrews.ac.uk/Extras/Hiawatha.html

]]>I often, in fact nearly always, have to refresh the page when I get to the blog just to see today’s post.

]]>http://statmodeling.stat.columbia.edu/2018/12/04/bayes-statistics-reproducibility-many-serious-problems-statistics-practice-arise-bayesian-inference-not-bayesian-enough-frequentist-evaluation-not-frequentist/#comment-922331

is most fitting here.

“any consensus about which challenges [methods] are important will change over time, so what we do in this decade, will not be the same as either what we did a few decades ago, or what we will do a few decades from now. … We live in a paradoxical world, where the only true safety, true though limited, comes from admitting both our uncertainty and the incompleteness with which we are able to meet it.”

]]>> the old statistics and the new statistics are the same statistics.

That is true of the subset of half baked new statistics that often involve ridiculous default priors.

At least in applications where t-tests and ANOVA are mostly OK.

But you get more opportunities (not less) for model hacking to keep supervisor/reviewers satisfied ;-)

]]>Bayes factors aren’t the same as a Bayesian analysis.

]]>I often find I need to “refresh” the page when I get to the blog – – otherwise, I don’t see comments posted since I last logged looked at the site.

]]>I do basic experimental work so all of my stuff is pretty much t-tests and ANOVA with varying degrees of p-hacking (on demand for my supervisor/reviewers). You can calculate effect sizes from my t and F statistics and degrees of freedom. You can convert from frequentist to Bayes Factors – there are R packages and online calculators for it.

Maybe for more sophisticated, larger and more complex datasets these things matter. But for me, the old statistics and the new statistics are the same statistics.

]]>If you have the number of comments per article available can you post an analysis of it by date? How much of an effect is this “timewarp” (as I’ve seen it called) having on the number of comments? If you have the data (no idea what you are logging), can you also do it by browser share?

]]>+0.1

;~)

]]>“No stops in any real science (that would just be a mirage of certainty), only pauses of unknown length.”

+1

]]>Or if the renowned Dr. Seuss went statistic. ]]>

Mark:

I dunno, 10 minutes? The hard part was writing the original, but Dr. Seuss did that. All I did was change a few words. “Savage McJeffreys McBean,” though . . . I’m proud of that. It scans just right!

]]>(Link is missing)

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