| Experimenter's Bias |
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Information AboutExperimenter's Bias |
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In principle, if a measurement has a resolution of , then if the experimenter averages 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 |
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