Sequential sampling is like a relationship. After a while, we can either accept it, reject it – or keep trying. Compared to its stodgy cousin, fixed size sampling, we are nimbly making a decision every step of the way. This method has a very big advantage over the fixed size approach: it often requires far fewer parts, yet provides the same statistical power. Fewer parts means it saves time, money, and most importantly, everyone's afternoon.
The method presented here was originally developed by Wald (1945) and is called the Sequential Probability Ratio Test (SPRT). We start out with an hypothesis of what we believe is the underlying defect rate of our population, p. Parts are sampled and tested one at a time and are determined to either pass or fail. After each measurement, we compare the observed %defect in our sample to decision thresholds calculated from SPRT theory and make a decision: accept our assumption about p, reject it, or keep on testing.It's a little like leaving a presentation after a few slides and saying, "OK, got it."
The operating characteristic (OC) curve for fixed sample sizes is compared to that from SPRT for various scenarios. A sequential sampling add-in available on the JMP Marketplace is used to facilitate comparisons between the two techniques. In this contest, SPRT can regularly best its cousin by offering improved efficiency and adaptability.
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