Ruud Wetzels

Best things in life are free

Prof. dr. Ruud Wetzels works as a Professor of Data Science at Nyenrode Business University. He is part of Nyenrode's Faculty Research Center for Accounting, Auditing & Control. 

Wetzels focuses on developing novel statistical methods for auditing and controlling. However, only developing methods will not change too much, therefore he also translate those methods into easy-to-use and free-of-charge software. Wetzels fill in the mission of Nyenrode by bridging the gap between academia and the business with a focus on data analytics.

Wetzels obtained his doctorate at the University of Amsterdam with a dissertation on Bayesian statistics and reinforcement learning. He has published over 35 academic articles and has been cited over 4,500 times.

Next to his academic work Wetzels works as a Director at PwC. Here he focuses on helping companies to work data-driven. This can mean developing and implementing a data strategy, implementing data management, or developing and implementing software that solves a business problem with data analytics or AI.  

Interests

Wetzels enjoys running, cycling, and bouldering.

Most relevant publications

• Wagenmakers, E.-J., Wetzels, R., Borsboom, D., & van der Maas, H. L. J. (2011). Why psychologists must change the way they analyze their data: The case of psi: Comment on Bem (2011). Journal of Personality and Social Psychology, 100(3), 426–432. 
• Wetzels, R. (2012, July 14). A default Bayesian hypothesis test for correlations and partial correlations. Psychonomic Bulletin & Review. 
• Wetzels, R., Vanderkerckhove, J., Tuerlinckx, F., & Wagenmakers, E.-J. (2009, January 13). Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task. ScienceDirect. 
• Derks, K., de Swart, J., Wagenmakers, E.-J., Wille, J., & Wetzels, R. (2021). JASP for Audit: Bayesian Tools for the Auditing Practice. Journal of Open Source Software, 6(68), 2733.
• Derks, K., de Swart, J., van Batenburg, P., Wagenmakers, E.-J., & Wetzels, R. (2021). Priors in a Bayesian audit: How integration of existing information into the prior distribution can improve audit transparency and efficiency. International Journal of Auditing, 25(3), 621-636.