

Statistical analysis of the NYT blog about font credibility - pjungwir
http://illuminatedcomputing.com/posts/2012/08/font-credibility/

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lmm
>I suppose we could keep running t-tests where the null hypothesis changes
from “Baskerville is the same as Comic Sans” to “Baskerville is 0.5 points
better than Comic Sans” to “Baskerville is 1 point better than Comic Sans,”
and get a range of probabilities. But a probability distribution like that
seems more like a Bayesian outcome; I’ve never heard of such a thing in
frequentist statistics.

That would essentially be a more detailed version of a confidence interval for
the actual difference - and since the distribution of the "actual value" is
almost certainly normal, it wouldn't really tell the reader anything more than
a regular one.

~~~
pjungwir
Hey, neat! Thank you for taking a moment to point that out. It's kind of cool
that just two values imply the entire probability distribution.

~~~
lmm
Well, only if it really is normal - and we already know any normal
distribution can be described by two parameters, mean and variance, so it
shouldn't be too surprising.

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pjungwir
Article author & submitter here: I wrote this post as self-assigned "homework"
to push my (very amateur) statistics knowledge. It responds to an article that
made HN last week, saying that font choice affects the believability of a
claim. I've love to learn more about how to do this kind of analysis, so feel
free to tear my post apart. :-)

