Systematic bias: Difference between revisions
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In [[metrology]], [[dynamical systems theory]], [[computational mechanics]], and [[statistics]], a '''systematic bias''' is a [[bias]] of a measurement system or estimate method, which leads to [[systematic error]]s, namely produces readings or results which are consistently too high or too low, relative to a given actual value of the measured or estimated variable. | In [[metrology]], [[dynamical systems theory]], [[computational mechanics]], and [[statistics]], a '''systematic bias''' is a [[bias]] of a measurement system or estimate method, which leads to [[systematic error]]s, namely produces readings or results which are consistently too high or too low, relative to a given actual value of the measured or estimated variable. | ||
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Latest revision as of 16:28, 20 August 2012
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In metrology, dynamical systems theory, computational mechanics, and statistics, a systematic bias is a bias of a measurement system or estimate method, which leads to systematic errors, namely produces readings or results which are consistently too high or too low, relative to a given actual value of the measured or estimated variable.
It is often used in exactly the same manner as the term systemic bias, though systematic is the older and more common form. Note, however, that while the word "systemic" in "systemic bias" means "caused by the system", the word "systematic" in "systematic error" merely means that the errors in question have a certain statistical tendency.
Systematic vs. random
An example of systematic bias would be the bias of a thermometer that always reads three degrees colder than the actual temperature because of an incorrect initial calibration or labelling, whereas one that gave random values within five degrees either side of the actual temperature would be considered a random error.
Once detected and quantified, it may be easy to compensate for a systematic bias. In the example just given, one knows that the thermometer always reads three degrees below the correct value. Thus, one can simply make a systematic correction by adding three degrees to all readings. In other cases, while a systematic bias is suspected or even detected, no simple correction may be possible because it can be impossible to quantify the error. Random errors can in some cases be reduced by repeating the experiment several times and considering an average result; in other cases repetition is not possible.
The existence and causes of systematic bias may be difficult to detect without an independent source of information; the phenomenon of scattered readings resulting from random error calls more attention to itself from repeated estimates of the same quantity than the mutually consistent incorrect results of a biased system.
The term systematic (or systemic) bias is sometimes be used to imply planned human agency. Systematic bias therefore can also mean that the system produces bias as a consequence of consistent, deliberate and planned human interference.
See also