I am not familiar with this (126.96.36.199 Laboratory Statistical Methods) clause. As you know, I do not do the QS thing on a regular basis. If you can e-mail me the text, perhaps I may have something that might help.
I do not know if this helps, but I submit them without a clue as to what assessors are looking for:
Paint Supplier: Supplier shipments indicate pigment content as average and variation. Which technique, if any, is used to verify the supplier’s data is within your capability of acceptance?
Molding OEM Supplier: Supplier shipments indicate melt flow as average and variation. Which technique, if any, is used that the supplier’s data is within your capability of acceptance?
Semiconductor Supplier: Series of shipments indicate the data are within +/- 1% of purchase order requirements. Which, if any, statistical technique would you use to verify this (sampling through destructive test, verification through inspection, etc., verification through regression analysis)?
Calibration Lab: The last three calibration CofC’s indicate average (actual) measurement as x.xxx +/- y.yyy. Which statistical technique would you use, if any, to verify if this measurement error was within your acceptable and submitted(?) MSA?
Molding Color Supplier: Supplier indicates a recommended Let Down Ratio (LDR) of 1.0%. Which statistical technique, if any, would you use to verify that a 1% ratio is acceptable to your color testing requirements?
Machine Shop: Shop ships a series of parts that use control charts as the acceptance mechanism in place. Charts indicate the process is in control and has a current capability of >1.65. Which statistical technique, if any, would you use to verify or accept this?
The paragraph in question leaves much open to interpretation (I know, interpretation is not supposed to be an issue, but it is). If I could offer a single suggestion, the QS procedures should be as generic as possible and use objective evidence (incoming inspection records) as compliance.
Do not know if this helps. QS is not my cup of tea, as I have said before. But, statistical analysis is a sorta well known subject. Best of luck. Perhaps a QS AND statistical person can shed additional light.
Of course, if I am completely off base, someone please let me know.