In capturing data for statistical analysis, be sure to retain the information contained in measurement data, as opposed to reducing it to a count.
Let's say our company operates a process for producing meat patties for quarter-pound hamburgers. We want 0.25 pound burgers. Our specification limits call for all burgers to be between 0.24 and 0.26 pounds. Anything outside those limits is considered a defect.
We test the process quality by capturing a sample of data. We could record the data by counting defects or by recording the actual measurement for each patty.
When we measure 2 patties, weighing 0.23 and 0.21 pounds, if we only counted defects, we would record only the number 2 -- for 2 defects. You can see how this loses information contained in the measurements.
0.23 and 0.21 pounds are not equally defective. Counting them equally as 1 defect apiece makes for a less accurate assessment of process quality.
So, to make the best use of the information contained in the data, we would do the analysis with measurement data, not counts.
Andrew A. (Andy) Jawlik is the author of the book, Statistics from A to Z -- Confusing Concepts Clarified, published by Wiley.