Continuous data is information that can be measured on a continuum or scale. Continuous data can have almost any numeric value and can be meaningfully subdivided into finer and finer increments, depending upon the precision of the measurement system.

As opposed to discrete data like good or bad, off or on, etc., continuous data can be recorded at many different points (length, size, width, time, temperature, cost, etc.). Continuous data is data that can be measured and broken down into smaller parts and still have meaning. Money, temperature and time are continuous. Volume (like volume of water or air) and size are continuous data.

Let’s say you are measuring the size of a marble. To be within specification, the marble must be at least 25mm but no bigger than 27mm. If you measure and simply count the number of marbles that are out of spec (good vs bad) you are collecting attribute data. However, if you are actually measuring each marble and recording the size (i.e. 25.2mm, 26.1mm, 27.5mm, etc) that’s continuous data, and you actually get more information about what you’re measuring from continuous data than from attribute data.

(Also see Discrete Data for alternative data type.)

(iSixSigma Dictionary)

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J. Jerrald Hayes
I am ex-architectural woodworker and general contractor turned IT, Business and Project Management consultant, software developer wannabe senior division triathlete and ski racer, Yankee fan and founder of, 360 Difference, and now too.
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