D
dsm_racing
I'm considering setting up a P chart to monitor mis-labeled samples coming into our lab. However, I'm not sure that I fully understand the tradeoffs involved when selecting a sigma. Could someone please tell me if this is right? If I choose a low sigma, then I am setting my UCL and LCL more narrow which will increase the probability that a point outside the limits is due to Type 1 error, however, if I set my sigma too high then I widen the limits and could be overlooking some assignable causes of variation?