Systematic Versus Random Error
Measurement errors can be divided into two components: random error and systematic error. Random error is always present in a measurement. It is caused by inherently unpredictable fluctuations in the readings of a measurement apparatus or in the experimenter's interpretation of the instrumental reading. Random errors show up as different results for ostensibly the same repeated measurement. They can be estimated by comparing multiple measurements, and reduced by averaging multiple measurements. Systematic error cannot be discovered this way because it always pushes the results in the same direction. If the cause of a systematic error can be identified, then it can usually be eliminated.
Because random errors are reduced by re-measurement (making n times as many measurements will usually reduce random errors by a factor of √n), it is worth repeating an experiment until random errors are similar in size to systematic errors. Additional measurements will be of little benefit, because the overall error cannot be reduced below the systematic error.
The Performance Test Standard PTC 19.1-2005 “Test Uncertainty”, published by the American Society of Mechanical Engineers (ASME), discusses systematic and random errors in considerable detail. In fact, it conceptualizes its basic uncertainty categories in these terms.
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Famous quotes containing the words systematic, random and/or error:
“Chinese civilisation is so systematic that wild animals have been abolished on principle.”
—Aleister Crowley (1875–1947)
“Man always made, and still makes, grotesque blunders in selecting and measuring forces, taken at random from the heap, but he never made a mistake in the value he set on the whole, which he symbolized as unity and worshipped as God. To this day, his attitude towards it has never changed, though science can no longer give to force a name.”
—Henry Brooks Adams (1838–1918)
“There are strange flowers of reason to match each error of the senses.”
—Louis Aragon (1897–1982)