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"Two

Making Sense of the Two-Proportions Test

Consider a production process that produced 10,000 widgets in January and experienced a total of 112 rejected widgets after a quality control inspection (i.e., failure rate = 1.12%). A Six Sigma project was deployed to fix this problem and by March the improvement plan was in place. In April, the process produced 8,000 widgets and experienced a total of 63 rejects (failure rate = 0.79%). Did the process indeed improve?
The appropriate hypothesis test for this question is the two-proportions test.

"Gage

Making Sense of Attribute Gage R&R Calculations

Measurement error is unavoidable. There will always be some measurement variation that is due to the measurement system itself.

Most problematic measurement system issues come from measuring attribute data in terms that rely on human judgment such as good/bad, pass/fail, etc. This is because it is very difficult for all testers to apply the same operational definition of what is “good” and what is “bad.”

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