[pymvpa] effect of signal on null distributions

[MS Al-Rawi]

> Here is the command he wrote to generate the dataset, where "mean" is what I previously called the "bias": 
> class A is generated by a normal distribution of with mean "mean", class B by a normal distribution of mean (-1 * "mean").

Two different means, one for class A, another for class B are more rational (than before).



>________________________________
> From: J.A. Etzel <jetzel at artsci.wustl.edu>
>To: pkg-exppsy-pymvpa at lists.alioth.debian.org 
>Sent: Wednesday, February 20, 2013 9:11 PM
>Subject: Re: [pymvpa] effect of signal on null distributions
> 
>Ben Acland (who recently joined our lab) ran this in pyMVPA, and it made a big difference in the resulting null distributions: they now are pretty much the same (permute training-only and permute both) even though the true-labeled accuracy changes drastically with the amount of signal.
>
>The post (with a bit more detail) is http://mvpa.blogspot.com/2013/02/pymvpa-null-distributions-different.html
>
>And here is a direct link to the results image http://3.bp.blogspot.com/-tnxhXSC7EvQ/USU2SxFD32I/AAAAAAAAARo/1wwf7RUFF60/s400/way.png
>
>So, yep, how we simulate the data really makes a difference.
>
>Jo
>
>
>
>
>On 2/13/2013 5:06 PM, J.A. Etzel wrote:
>> What do the null distribution for different amounts of signal look like
>> if you try the simulations making the data as I describe (values from
>> two normal distributions with a small difference in mean but same
>> standard deviation)?
>
>
>-- Joset A. Etzel, Ph.D.
>Research Analyst
>Cognitive Control & Psychopathology Lab
>Washington University in St. Louis
>http://mvpa.blogspot.com/
>
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