posted 02 June 1999 01:06 PM

There are various procedures for calculating sample size, depending upon your application and methods. The one I gave is for attribute data. The equation I cited above is from "Handbook of Statistical Methods in Manufacturing" by Clements (pp. 43), the "CQE Primer" by the Quality Council of Indiana (pp. XI-10) and "Statistical Techniques in Business and Economics" by Mason (pp. 379-385). The latter reference gives the derivation of the equation (although you have to search through the text for it), for those interested. While the variable definitions above are from Clements, the "CQE Primer" does give slightly different ones (below):E = The desired proportion interval

p = Proportion rate

"Statistical Techniques in Business and Economics" gives the following definitions for p and E.

E = The maximum allowable error the researcher will tolerate.

p = The estimated proportion based on past experience, or a pilot survey.

From the references, Clements uses 'p' and the other two use 'p-bar' as the variables. While I prefer p-bar, my original post was from Clements, so it used his variables and definitions.

quote:

If you were to use p for your maximum tolerable proportion nonconforming the formula would give you smaller sample sizes as you tightened your tolerances.

The sample size goes down as the "tolerable or maximum" percentage nonconforming goes down. The equation does not consider tolerances in its calculation of sample size. The smaller the number of nonconforming items in the lot, the required sample size to accept or reject the lot goes down, as I understand its use. Of course, there are other things to consider when selecting sample size, but these are covered well in the references and would be redundant here.

quote:

p = the historical or estimated proportion nonconforming, and E = the tolerable proportion nonconforming.

As you can see from above, the published references gave different definitions. I am sure other definitions exist elsewhere as well.

Does this help, or did I just muddy the water?

Regards,

Don

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