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.
Other articles related to "common":
... 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 ...
Famous quotes containing the words common and/or special:
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“The gap between ideals and actualities, between dreams and achievements, the gap that can spur strong men to increased exertions, but can break the spirit of othersthis gap is the most conspicuous, continuous land mark in American history. It is conspicuous and continuous not because Americans achieve little, but because they dream grandly. The gap is a standing reproach to Americans; but it marks them off as a special and singularly admirable community among the worlds peoples.”
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