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
Famous quotes containing the words common and/or special:
“There ought to be an absolute dictatorship ... a dictatorship of painters ... a dictatorship of one painter ... to suppress all those who have betrayed us, to suppress the cheaters, to suppress the tricks, to suppress mannerisms, to suppress charms, to suppress history, to suppress a heap of other things. But common sense always gets away with it. Above all, lets have a revolution against that!”
—Pablo Picasso (18811973)
“The treatment of the incident of the assault upon the sailors of the Baltimore is so conciliatory and friendly that I am of the opinion that there is a good prospect that the differences growing out of that serious affair can now be adjusted upon terms satisfactory to this Government by the usual methods and without special powers from Congress.”
—Benjamin Harrison (18331901)