Interpretation of Data
Identical observations are often interpreted differently by different scientists, and that fact and its implications are the subject of this chapter. Interpretation effects are most simply defined as any difference in interpretations. The difference may be between two or more interpreters, or an interpreter and such a generalized interpreter as an established theory or an “accepted” interpretation of a cumulative series of studies. As in the observer effect, the interpreter effect, or difference, does not necessarily imply a unidirectional phenomenon. When observations are nonrandomly distributed around a true value, these are referred to as “biased observations.” Similarly, when interpretations do not vary randomly—and usually they do not—these are referred to as “biased”.
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