Against Coherence: Truth, Probability, and Justification by Erik J. Olsson

By Erik J. Olsson

It's tempting to imagine that, if a person's ideals are coherent, also they are more likely to be precise. This fact conduciveness declare is the cornerstone of the preferred coherence conception of data and justification. Erik Olsson's new e-book is the main vast and targeted research of coherence and possible fact thus far. surroundings new criteria of precision and readability, Olsson argues that the price of coherence has been largely over priced. Provocative and readable, opposed to Coherence will make stimulating studying for epistemologists and someone with a significant curiosity honestly.

Show description

Read or Download Against Coherence: Truth, Probability, and Justification PDF

Best probability books

Probability and Theory of Errors (Fourth Edition)

This can be a pre-1923 ancient replica that was once curated for caliber. caliber insurance used to be performed on each one of those books in an try to eliminate books with imperfections brought by means of the digitization technique. notwithstanding we've made most sensible efforts - the books could have occasional error that don't abate the studying event.

Quantum Probability and Related Topics: Proceedings of the 30th Conference

This quantity includes present paintings on the frontiers of study in quantum chance, endless dimensional stochastic research, quantum info and information. It offers a gently selected selection of articles through specialists to focus on the newest d

Additional info for Against Coherence: Truth, Probability, and Justification

Sample text

This intuition admits of simple probabilistic verification, as shown in Goldman (2001). Although some independence is necessary for agreement to be significant, it is clear that the witnesses need not be completely independent for this to happen. L. Jonathan Cohen’s well-known corroboration theorem establishes the truth of this preconception in probabilistic terms (1977: 101–7). As Cohen notes, it may be true of each of two positively relevant testimonies that neither corroborates the other. Thus, we might have (1) P(H/E1) > P(H ) and (2) P(H/E2) > P(H ) without having either (2C1) P(H/E2,E1) > P(H/E1) or (1C2) P(H/E1,E2) > P(H/E2).

Two testimonies are conditionally independent just in case, once the truth-value of the hypothesis is known, what the one witness has said does not affect the probability of what the other witness will say. The assumption of conditional independence has two parts, corresponding to assuming the hypothesis true or assuming it false: P(E1/H ) ¼ P(E1/H,E2) and PðE1 =:HÞ ¼ PðE1 =:H, E2 Þ. These two assumptions serve to simplify calculations tremendously and yet this is not their main motivation. e. 14 What reasons are there for thinking that conditional independence in the sense just referred to is an adequate probabilistic representation of testimonial independence?

Before we have queried the reporters, we do not know which hypothesis to accept. However, upon observing the agreement, we become more inclined to think that the witnesses are telling the truth, as agreement would be highly unlikely on the alternative hypothesis of a mere random selection. As an effect of the increased probability of reliability, we also become more confident that what the reports say is true. Needless to say, none of this should be taken to imply that there is a need to revise the prior probability of the reliability hypothesis because of congruence.

Download PDF sample

Rated 4.97 of 5 – based on 22 votes