Experimenter's bias
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Experimenter's bias is the phenomenon in experimental science by which the outcome of an experiment tends to be biased towards a result expected by the human experimenter. The inability of a human being to remain completely objective is the ultimate source of this bias. It occurs more often in sociological and medical sciences, for which reason double blind techniques are often employed to combat the bias. But experimenter's bias can also be found in some physical sciences, where the experimenter rounds-off measurements. If the signal being measured is actually smaller than the rounding error and the data are over-averaged, a positive result for the measurement can be found in the data where none exists (i.e. a more precise experimental apparatus would conclusively show no such signal).
In principle, if a measurement has a resolution of R, then if the experimenter averages N independent measurements the average will have a resolution of
(this is the central limit theorem of statistics). This is an important experimental technique used to reduce the impact of randomness on an experiment's outcome. But note that this requires that the measurements be statistically independent, and there are several reasons why that independence may fail. If it does then the average may not actually be a better measurement but may merely reflect the correlations among the individual measurements and their non-independent nature.
The most common cause of non-independence is systematic errors (errors affecting all measurements equally, causing the different measurements to be highly correlated, so the average is no better than any single measurement). But another cause can be due to the inability of a human observer to round off measurements in a truly random manner. If an experiment is searching for a sidereal variation of some measurement, and if the measurement is rounded-off by a human who knows the sidereal time of the measurement, and if hundreds of measurements are averaged to extract a "signal" which is smaller than the apparatus' actual resolution, then it should be clear that this "signal" can come from the non-random round-off, and not from the apparatus itself. In such cases a single-blind experimental protocol is required; if the human observer does not know the sidereal time of the measurements, then even though the round-off is non-random it cannot introduce a spurious sidereal variation.
Note that modern electronic or computerized data acquisition techniques have greatly reduced the likelihood of such bias, but it can still be introduced by a poorly-designed analysis technique. Experimenter's bias was not well recognized until the 1950's and 60's, and then it was primarily in medical experiments and studies. Its effects on experiments in the physical sciences have not always been fully recognized.
See also
Acknowledgement and Attribution Regarding Sources of Content
Some of the initial content on this page may be incorporated in part from copyleft sources in the public domain including wikis such as Wikipedia and AskDrWiki. Drug information for patients came from the The National Library of Medicine. Infectious disease information may have come from the Centers for Disease Control (CDC). Differential Diagnoses are drawn from clinicians as well as an amalgamation of 3 sources: 1.The Disease Database; 2. Kahan, Scott, Smith, Ellen G. In A Page: Signs and Symptoms. Malden, Massachusetts: Blackwell Publishing, 2004:3; 3. Sailer, Christian, Wasner, Susanne. Differential Diagnosis Pocket. Hermosa Beach, CA: Borm Bruckmeir Publishing LLC, 2002:7 .

