Measurement of Subjective Probability

"Beliefs come in degrees, and we often represent those degrees with numbers. We might say, for example, that we are 90 per cent confident in the truth of some scientific hypothesis, or only 30 per cent confident in the success of some risky endeavour. But what do these numbers mean? What, in other words, is the underlying psychological reality to which the numbers correspond? And what constitutes a meaningful difference between numerically distinct representations of belief? This Element discusses the main approaches to the measurement of belief. These fall into two broad categories - epistemic and decision-theoretic - with divergent foundations in the theory of measurement. Epistemic approaches explain the measurement of belief by appeal to relations between belief states themselves, whereas decision-theoretic approaches appeal to relations between beliefs and desires in the production of choice and preferences"--

List of contents

1. Introduction; 2. Representation and measurement; 3. Clarifications and desiderata; 4. Epistemic approaches: comparative confidence; 5. Epistemic approaches: alternatives; 6. Decision-theoretic approaches; Bibliography.

Summary

This Element discusses the main approaches to the measurement of belief. Epistemic approaches explain the measurement of belief by appeal to relations between belief states themselves, whereas decision-theoretic approaches appeal to relations between beliefs and desires in the production of choice and preference.

Foreword

The theory of measurement applied to the probabilistic representation of belief.

Product details

• Authors: Edward J. R. Elliott, Edward J. R. (University of Leeds) Elliott
• Publisher: Cambridge University Press ELT
• Languages: English
• Product format: Hardback
• Released: 30.06.2024
• EAN: 9781009486965
• ISBN: 978-1-0-0948696-5
• No. of pages: 75
• Series: Elements in Decision Theory and Philosophy
• Subjects: Non-fiction book > Philosophy, religion > Philosophy: general, reference works; Social sciences, law, business > Business > Business administration; PHILOSOPHY / General, Probability & statistics, Philosophy: logic, Probability and statistics, Decision theory: general