Hypothesis Evaluation Using the Bayes Factor

 by Herbert Hoijtink

University Utrecht



This workshop will introduce the participants to null hypothesis significance testing and its role in the replication crisis. Subsequently, an alternative, hypothesis evaluation using the Bayes factor will be introduced. It will be elaborated what the Bayes factor is, how it can be applied and should be interpreted. There will be attention for Bayesian updating (an alternative for power analysis), Bayesian (conditional) error probabilities and limitations of the approach.


This workshop is tailored to participants that want to use their own data to evaluate hypotheses using the Bayes factor instead of the p-value. Therefore this workshop is NOT technical in nature (there are virtually no formulas that will be discussed) BUT it is applied (what can it do, how can you execute it, and how should you interpret the results).

Participants Have to Prepare by

  1. Installing the R package on their computer (
  2. Installing R Studio on their computer (
  3. Downloading Bain-0.1.0 from use the Bain button
  4. Unzip Bain-0.1.0, read the installation instructions and install Bain


  1. Read the tutorial contained in the Bain Zip file
  2. Download the workshop slide from use the Bain button


July 12th 13.00-19.00

13.00-14.00    A Crash Course in R (hands on the computer)

14.00-14.15    Break

14.15-15.15    Null Hypothesis Significance Testing and its Role in the Replication Crisis

15.15-15.30    Break

15.30-16.30    Replacing the Null and Alternative Hypotheses by Informative Hypotheses AND Replacing the p-value by the Bayes Factor

16.30-17.00    Break

17.00-18.00    Hypothesis Evaluation Using the R package Bain (hands on the computer TUTORIAL STEP 1-2-7-9)

18.00-19.00    Interpreting the Size of the Bayes Factor, Questions and Wrap up


July 13th  9.00-13.00

 9.00-10.30     Bayesian Updating, Posterior Model Probabilities and Conditional Error Probabilities

10.30-10.45    Break

10.45-11.45    Bayesian Updating Using the R package Bain(hands on the computer TUTORIAL STEP 11)

11.45-12.00    Break

12.00-13.00    Criticising the Bayesian Approach, Prior Sensitivity, Questions and Wrap up