My last column, “Dealing With Count Data and Variation,” showed how a matrix presentation of stratified count data could be quite effective as a common-cause strategy. I’ll use this column to review some key concepts of count data as well as to demonstrate the first of two common statistical techniques that can be useful for further analysis. Obtaining the counts themselves is only half of the job.

First, make sure the operational definition is clear: What’s the threshold whereby something goes from a “nonincident” (i.e., a value of 0) to an “incident” (i.e., a value of 1)? Would two or more people assessing the situation concur that the “incident” had occurred?

In addition, all count data have an implicit denominator that’s defined by the “area of opportunity” for that count. It depends on what's being counted, how it’s being counted, and what possible restrictions there might be upon the count.

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