compared performance of two groups given the same task (rating portrait pictures and estimating how successful each individual was on a scale of −10 to 10), but with different experimenter expectations. In one group, ("Group A"), experimenters were told to expect positive ratings while in another group, ("Group B"), experimenters were told to expect negative ratings. Data collected from Group A was a significant and substantially more optimistic appraisal than the data collected from Group B. The researchers suggested that experimenters gave subtle but clear cues with which the subjects complied. Prevention Double blind techniques may be employed to combat bias by causing the experimenter and subject to be ignorant of which condition data flows from. It might be thought that, due to the central limit theorem of statistics, collecting more independent measurements will improve the precision of estimates, thus decreasing bias. However, this assumes that the measurements are statistically independent. In the case of experimenter bias, the measures share correlated bias: simply averaging such data will not lead to a better statistic but may merely reflect the correlations among the individual measurements and their non-independent nature. See also List of cognitive biases Allegiance bias Cultural bias Demand characteristics Epistemic feedback Funding bias Hawthorne effect N rays – imaginary radiation Naturalistic observation Observer bias Participant observer Placebo and Nocebo Publication bias Pygmalion effect – teachers who expect higher achievement from some children actually get it Reality tunnel Reflexivity (social theory) Subject-expectancy effect Systematic bias White-hat bias References External links Skeptic's Dictionary on the Experimenter Effect Design of experiments Cognitive inertia