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:
“... every woman’s organization recognizes that reformers are far more common than feminists, that the passion to look after your fellow man, and especially woman, to do good to her in your way is far more common than the desire to put into every one’s hand the power to look after themselves.”
—Crystal Eastman (1881–1928)
“We’ve got to figure these things a little bit different than most people. Y’know, there’s something about going out in a plane that beats any other way.... A guy that washes out at the controls of his own ship, well, he goes down doing the thing that he loved the best. It seems to me that that’s a very special way to die.”
—Dalton Trumbo (1905–1976)