Bias in Scientific Studies
In empirical science, bias is any factor that may systematically distort quantitative or qualitative conclusions and recommendations. Psychological sources of biases have separate encyclopedia entries.
Bias must be distinguished from fraud, oversights, misunderstandings, and nonsense arithmetic. It must further be distinguished from the field of statistical pitfalls, illusions, and paradoxes, though each of these, when unrecognized, may bias perceptions and recommendations.
The classical borderline between random error and bias is sometimes fuzzy. The label “bias” is often used about poor data recording, regardless of whether it will affect conclusions and, if so, how. Moreover, blunt procedures (imprecise measurements) may delay the recognition of a health hazard, or benefit, and in that sense pure randomness is itself “biased” against public interests.
Recognition of Bias
Just as, while there is no ...