[SciPy-User] "small data" statistics
josef.pktd@gmai...
josef.pktd@gmai...
Sat Oct 13 08:07:47 CDT 2012
On Thu, Oct 11, 2012 at 10:57 AM, <josef.pktd@gmail.com> wrote:
> Most statistical tests and statistical inference in scipy.stats and
> statsmodels relies on large number assumptions.
>
> Everyone is talking about "Big data", but is anyone still interested
> in doing small sample statistics in python.
>
> I'd like to know whether it's worth spending any time on general
> purpose small sample statistics.
>
> for example:
>
> http://facultyweb.berry.edu/vbissonnette/statshw/doc/perm_2bs.html
>
> ```
> Example homework problem:
> Twenty participants were given a list of 20 words to process. The 20
> participants were randomly assigned to one of two treatment
> conditions. Half were instructed to count the number of vowels in each
> word (shallow processing). Half were instructed to judge whether the
> object described by each word would be useful if one were stranded on
> a desert island (deep processing). After a brief distractor task, all
> subjects were given a surprise free recall task. The number of words
> correctly recalled was recorded for each subject. Here are the data:
>
> Shallow Processing: 13 12 11 9 11 13 14 14 14 15
> Deep Processing: 12 15 14 14 13 12 15 14 16 17
> ```
example: R package coin
http://cran.r-project.org/web/packages/coin/vignettes/coin.pdf
found again while digging for an error in p-values in stats.wilcoxon
in the presence of ties https://github.com/scipy/scipy/pull/338
and enhancements for it.
Josef
> Josef
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