As Davis Balestracci frequently emphasized in his column, “RealWorldSPC,” published in Quality Digest for four years, it is fundamental to understand the context of the data before you begin to do any computations. It is the background for your data that determines how you should organize the data, how you should analyze the data, and how you should interpret the results of your analysis. Once you ignore the context, you’re like a train that has gone off the track, with the inevitable result.

One day a company sent me some data that it had spent more than a month collecting. These data represented the results of an experimental study carried out using production batches. For each of 30 batches the company recorded all sorts of production information, along with the experimental conditions that applied to that batch. At the end of the production process it took 40 items from each batch and measured the property of interest. Thus, it had a total to 1,200 values: 40 values for each of the 30 batches.

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