1

I am trying to control a binomial proportion that hovers pretty close around 0.1% - 1.0%. Since it seems like dropping from 0.1% to 0.05% is equally as severe as increasing to 0.2% (halving the occurrences, doubling the occurrences), it makes sense to me to use geometric mean / standard deviation. Also, by using geometric standard deviation, it seems I have an added benefit of not having the lower limit become less that 0.0% (an impossible value for my data).

Are there any examples that support using geometric calculations in statistical process control or is it a bad idea altogether?

Tim Harper
  • 121
  • This sounds like a transformation of the measurement. My understanding is that first you prove stability in your measure (whatever it is) then you compute control limits. The limit computation, like Levey-Jennings, is textbook. The dial you can change is the measure itself. It sounds like you are looking for the logarithm base-2 of a proportion.

    Could you supply sample (or synthetic) data here to allow a guy to show an approach on what you consider reasonable data?

     – EngrStudent Mar 18 '14 at 22:48

0 Answers0