Common Cause and Special Cause (statistics)

Common Cause And Special Cause (statistics)

Common and special causes are the two distinct origins of variation in a process, as defined in the statistical thinking and methods of Walter A. Shewhart and W. Edwards Deming. Briefly, "common causes" are the usual, historical, quantifiable variation in a system, while "special causes" are unusual, not previously observed, non-quantifiable variation.

The distinction is fundamental in philosophy of statistics and philosophy of probability, with different treatment of these issues being a classic issue of probability interpretations, being recognised and discussed as early as 1703 by Gottfried Leibniz; various alternative names have been used over the years.

The distinction has been particularly important in the thinking of economists Frank Knight, John Maynard Keynes and G. L. S. Shackle.

Read more about Common Cause And Special Cause (statistics):  Origins and Concepts, Importance To Economics, Importance To Industrial and Quality Management, In Engineering

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Common Cause And Special Cause (statistics) - In Engineering
... Commonmode, or commoncause, failure has a more specific meaning in engineering ... But even so there can be many commonmodes consider a RAID1 where two disks are purchased online and are installed in a computer, there can be many ... Strategies for the avoidance of commonmode failures include keeping redundant components physically isolated ...

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