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Belief, Evidence, and UncertaintyIntroductory Remarks—Inferential Uncertainty

Belief, Evidence, and Uncertainty: Introductory Remarks—Inferential Uncertainty [Most of the claims we make, nowhere more so than in the empirical sciences, outrun the information enlisted to support them. Such claims are never more than probable/likely. Intuitively, even obviously, some claims are more probable/likely than others. Everyone agrees that scientific claims in particular are probable/likely to the extent that they are confirmed by experimental evidence. But there is very little agreement about what “confirmation by empirical evidence” involves or how it is to be measured. A central thesis of this monograph is that a source of this disagreement is the near-universal tendency to conflate the two different concepts—“confirmation” and “evidence”—used to formulate the essence of the methodology. There is no doubt that the words signifying them are used interchangeably. But as we will go on to argue, failure to make the distinction leads to muddled thinking in philosophy, statistics, and the empirical sciences themselves. Two examples, one having to do with the testing of traditional psychotherapeutic hypotheses, the other with determining the empirical superiority of the wave or particle theories of light, make it clear how data can confirm a hypothesis or theory, yet fail, in context, to provide evidence for it.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Belief, Evidence, and UncertaintyIntroductory Remarks—Inferential Uncertainty

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Publisher
Springer International Publishing
Copyright
© The Author(s) 2016
ISBN
978-3-319-27770-7
Pages
3 –13
DOI
10.1007/978-3-319-27772-1_1
Publisher site
See Chapter on Publisher Site

Abstract

[Most of the claims we make, nowhere more so than in the empirical sciences, outrun the information enlisted to support them. Such claims are never more than probable/likely. Intuitively, even obviously, some claims are more probable/likely than others. Everyone agrees that scientific claims in particular are probable/likely to the extent that they are confirmed by experimental evidence. But there is very little agreement about what “confirmation by empirical evidence” involves or how it is to be measured. A central thesis of this monograph is that a source of this disagreement is the near-universal tendency to conflate the two different concepts—“confirmation” and “evidence”—used to formulate the essence of the methodology. There is no doubt that the words signifying them are used interchangeably. But as we will go on to argue, failure to make the distinction leads to muddled thinking in philosophy, statistics, and the empirical sciences themselves. Two examples, one having to do with the testing of traditional psychotherapeutic hypotheses, the other with determining the empirical superiority of the wave or particle theories of light, make it clear how data can confirm a hypothesis or theory, yet fail, in context, to provide evidence for it.]

Published: Mar 5, 2016

Keywords: Belief; Evidence; Inferential uncertainty; Dodo bird verdict; Poisson spot

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