Back to results

Massachusetts Institute of Technology

Justifying Bayesianism

Abstract

dc:description.abstract

Bayesianism, in its traditional form, consists of two claims about rational credences. According to the first claim, probabilism, rational credences form a probability function. According to the second claim, conditionalization, rational credences update by conditionalizing on new evidence. The simplicity and elegance of classical Bayesianism make it an attractive view. But many have argued that this simplicity comes at a cost: that it requires too many idealizations. This thesis aims to provide a justification of classical Bayesianism. Chapter One defends probabilism, classically understood, against the charge that by requiring credences to be precise real numbers, classical Bayesianism is committed to an overly precise conception of evidence. Chapter Two defends conditionalization, classically understood, against the charge that epistemic rationality consists only of synchronic norms. Chapter Three defends both probabilism and conditionalization against the objection that they require us, in some circumstances, to have credences that we can know are not as close to the truth as alternatives that violate Bayesian norms.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Linguistics and Philosophy.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Carr, Jennifer Rose
Advisor dc:contributor.advisor
  • Richard Holton.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/84415
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/84415

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Carr, Jennifer Rose. Justifying Bayesianism. Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/84415