Most researchers in the social and behavioral sciences will probably have heard of Bayesian statistics in which probability is defined differently compared to classical statistics (probability as the long-run frequency versus probability as the subjective experience of uncertainty). At the same time, many may be unsure of whether they should or would like to use Bayesian methods to answer their research questions (note: all types of conventional questions can also be addressed with Bayesian statistics). As an attempt to track how popular the methods are, we searched all papers published in 2013 in the field of Psychology (source: Scopus), and we identified 79 empirical papers that used Bayesian methods (see e.g. Dalley, Pollet, & Vidal, 2013; Fife, Weaver, Cool, & Stump, 2013; Ng, Ntoumanis, Thøgersen-Ntoumani, Stott, & Hindle, 2013) . Although this is less than 0.5% of the total number of papers published in this particular field, the fact that ten years ago this number was only 42 indicates that Bayesian methods are slowly beginning to creep into the social and behavioral sciences.

The current paper aims to get you started working with Bayesian statistics. We provide:

  1. a brief introduction to Bayesian statistics,
  2. arguments as to why one might use Bayesian statistics,
  3. a reading guide used to start learning more about Bayesian analyses, and, finally
  4. guidelines on how to report Bayesian results.

Van de Schoot, R., & Depaoli, S. (2014). Bayesian analyses: where to start and what to report. The European Health Psychologist, 16(2), 75-84. Retrieved from http://www.ehps.net/ehp/index.php/contents/issue/view/ehp.v16.i2/showToc