Bayes data analysis in the social sciences curriculum: a review

Fine, Philip A. (2018) Bayes data analysis in the social sciences curriculum: a review. Cognitive Psychology Bulletin (3). ISSN 2397-2661 (In Press)

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Abstract

In September 2017, I attended 'Bayesian Data Analysis in the Social Sciences Curriculum', a one-day conference organised by Thom Baguley and Mark Andrews (Nottingham Trent University), marking the culmination of a 3-year ESRC funded programme on Bayesian Data Analysis. The core of this programme was an annual series of 4 workshops (www.priorexposure.org.uk), and the conference delegates included workshop graduates alongside Bayesian newbies like myself. Essentially, Bayesian data analysis is an alternative to 'classical' or 'frequentist' null hypothesis significance testing (NHST), based on probabilistic reasoning (Dienes, 2008, Andrews, 2016). Neither frequentist nor Bayesian analysis are right or wrong: they are different approaches to how scientific inference can be drawn from data sets.

Item Type: Article
Additional Information: This was a review of a 1 day conference on using Bayes Data Analysis in Psychology and other Social Sciences. This is a Prepublication Version of the following article: Fine, P.A. (2018), Bayes Data Analysis in the Social Sciences Curriculum: A Review. The Cognitive Psychology Bulletin, Issue 3. BPS.
Uncontrolled Keywords: Bayesian Data Analysis; conference review
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Q Science > QA Mathematics
Divisions: School of Psychology and Wellbeing
Depositing User: Philip Fine
Date Deposited: 12 Jan 2018 15:38
Last Modified: 10 Dec 2019 11:26
URI: http://bear.buckingham.ac.uk/id/eprint/238

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