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 |
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| 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: | 29 Jun 2023 09:20 |
| URI: | http://bear.buckingham.ac.uk/id/eprint/238 |
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