What kind of data?

A quick-and-dirty guide to variables, attributes data

The short story about data describes variables data as that which is acquired through measurements. This can be length, time, diameter, strength, weight, temperature, density, thickness, pressure, or height. Accuracy can be measured, for example, to the nearest inch, centimeter, millimeter, or micron.

Attributes data, on the other hand, can be classified and counted. The language connected with each kind of data is slightly different. With variables data, one is interested in central location and spread, showing data in relation to the process average and piece-by-piece variation. In attributes data, key concepts are “nonconformities” and “nonconforming.” This may sound like a semantic distinction, but in fact, for nonconformities, data is counted in terms of defects per item or group of items, while nonconforming data includes counts of defective items.

Examples:

Variables data: window size, closing time, tire pressure, glass thickness, daily weight gain/loss.

Attributes data: errors on math test or blood test; invoice problems (nonconformities); broken or missing parts; numbers of employees absent; broken glass products (nonconforming).

Originally published in the November 2010 edition of Quality eLine, our free monthly newletter.

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