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'[EE] Large statistical datasets in electronics-rel'
2007\11\21@124610 by Marcel Birthelmer

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Hi all,
I'm currently preparing for a term project in my "Engineering
Statistics" class, the goal of which is to analyze a large (thousands
of samples) dataset. I would very much like to direct my efforts at an
electronics-related project, but I've had a hard time finding datasets
of any sort of substance there.
So I turn to the list in my time of need once more, hoping that
someone, maybe those of you involved in fab or manufacturing
processes, would have access to a significant amount of statistical
data relating to process parameters, component parameters, yield, etc.
that you would not mind sharing.
Thanks for your help,
- Marcel

2007\11\21@133603 by Marcel Duchamp

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Marcel Birthelmer wrote:
> Hi all,
> I'm currently preparing for a term project in my "Engineering
> Statistics" class, the goal of which is to analyze a large (thousands
> of samples) dataset. I would very much like to direct my efforts at an
> electronics-related project, but I've had a hard time finding datasets
> of any sort of substance there.
> So I turn to the list in my time of need once more, hoping that
> someone, maybe those of you involved in fab or manufacturing
> processes, would have access to a significant amount of statistical
> data relating to process parameters, component parameters, yield, etc.
> that you would not mind sharing.
> Thanks for your help,
> - Marcel

I do not have a ready to go database of statistical data for you but
here's a suggestion that comes to mind after the discussion a few weeks
ago here on random number generators.  This is a topic whose venn
diagram lines up perfectly with "Engineering Statistics" I would think.

Some approaches.  Build a zener diode white noise generator and sample
it with the output going to a file.  You should be able to get a very
large file of data in a short time and then be able to analyze it.

Or analyze the software versions (prng) and point out the shortcomings
of each based on long term analysis.  Once they wrap around, an fft will
show their lack of randomness.

That's all that comes to mind right now; I did not take that class in
college.  We had to drink beer instead.

2007\11\21@140556 by Marcel Birthelmer

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On Nov 21, 2007 10:34 AM, Marcel Duchamp <spam_OUTmarcel.duchampTakeThisOuTspamsbcglobal.net> wrote:
{Quote hidden}

> -

2007\11\21@144228 by Marcel Duchamp

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Marcel Birthelmer wrote:
>  But
> yes, if you (or anyone else) have an idea about how to meaningfully
> analyze the data from a noise generator (to keep it in the EE realm),
> that would be a good approach.
> Thanks,
> - Marcel

My knowledge here is very shallow.  But wikipedia has some information
as well as links to material that should help out a bit.

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