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allows us to get to the root cause of things and address that because I think the discussion today has been mainly on the statistical aspect of that.  I don't think that's a complete picture for discussion.

I think the manufacturing process, understanding the physics of that aspect, has to be sort of brought in.  So I think that's the reason we wanted to bring this up as an awareness topic and get your feedback so that we can prepare well when we bring this back again.

DR. KIBBE:  Thank you, Ajaz.

I have just a couple of thoughts and that is, the sample size is proposed at 12 and 36, one tier, two tier.  That would apply to a batch run of 1,000 samples, a batch run of 10,000, a batch run of a 100,000, and have you looked at the statistical ability to actually detect, with the same confidence, potential outliers and errors in larger batches with a fixed sampling size?

MR. SCHUIRMANN:  It strikes many as counterintuitive, but the performance of the test really doesn't depend much on the size of the batch, unless the the number in your sample starts to become a non-trivial proportion of the number in your manufactured batch.  

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