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”.
Keywords: interpreter effects, data interpretation, physical sciences, biological sciences, behavioral sciences
Oxford Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.
Please, subscribe or login to access full text content.
If you think you should have access to this title, please contact your librarian.
To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us .