Software and other tools
Tools for statisticians
Our team is active in developing statistical software and support resources to equip both the beginner and experienced user to perform Bayesian and other analyses.
- Bayes Factor Calculator
- The Bayesplay R Package and Web-app
Developed by Dr Lincoln Colling, the Bayesplay R package and web-app allow you to flexibly combine different likelihoods and priors to compute a range of different types of Bayes factors. Using Bayesplay, it is possible to compute Bayes factors of the type advocated by Prof Dienes, as well as perform the Default Bayesian t-tests advocated by Rouder, Speckman, Sun, and Morey (2008) and Informed Bayesian t-tests advocated by Gronau, Ly, & Wagenmarkers (2020). These analyses can be performed within a single unified modelling framework. Analyses can be performed directly in R using the Bayesplay package or using the web-app. The web-app can generate the appropriate code for performing the analyses in R, which is useful for inexperienced R users. The Bayesplay package is also accessible through the JASP statistics package.
- adventr and discovr Tutorials
Prof Andy Field has released two R packages that contain interactive tutorials for learning about statistics and R. These are the adventr and discovr packages. These packages also serve as companions to Prof Field’s statistics textbooks. adventr is the companion to An Adventure in Statistics: The Reality Enigma and discovr is a companion to the forthcoming Discovering Statistics Using R and R Studio (2nd edition).
- R Package and RMarkdown Thesis Template
Dr Danielle Evans has released an R package for Sussex University PhD students interested in writing their thesis in RMarkdown, with associated template.