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Re: st: Interpretation of Two-sample t test with equal variances?


From   "JVerkuilen (Gmail)" <jvverkuilen@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Interpretation of Two-sample t test with equal variances?
Date   Wed, 20 Mar 2013 19:19:55 -0400

On Wed, Mar 20, 2013 at 3:22 PM, David Hoaglin <dchoaglin@gmail.com> wrote:
> Jay,
>
> I'm not aware that boxplots make any assumptions.  They show what they
> are intended to show.  Their "performance" comes from the way people
> interpret them.  Boxplots of skewed data will tend to have certain
> characteristics, boxplots of light-tailed data will have other
> characteristics, and so on.  Some patterns suggest bimodal data.

Oh definitely they show what they were intended to show, and they are
incredibly useful, but the way we teach them I think leads many folks
down the garden path. The assumptions I'm thinking of include ones
such as the largely unstated background assumption that outliers are
an issue. I've become adept at recognizing when a boxplot is giving me
a light tailed distribution because the box ends up being too big, but
if you have multiple modes that will get blown away and they provide
too much reduction.
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