Survey data, simulation data, and Python codes for building a Bayesian hierarchical hypothesis testing model in a maturity assessment study

Published: 24 May 2023| Version 1 | DOI: 10.17632/hzk5fwpbxs.1
Serdar Semih Coşkun


This supplementary material involves survey data and Python codes that prescribe Bayesian hypothesis testing applications in a scientific study. The simulation data has been generated by Markov Chain Monte Carlo analysis to test the Bayesian mean differences between the process improvement practitioner and non-practitioner companies over the procurement maturity dimensions. It will be more tractable when you first read the paper and then run the codes by yourself. Here, is the reference: Coşkun, S. S., & Kazan, H. (2023). Bayesian analysis of the relationship between process improvement practices and procurement maturity. Computers & Industrial Engineering, 181, 109297.



Istanbul Universitesi Iktisat Fakultesi


Markov Chain Monte Carlo, Bayesian Statistics, Bayesian Hierarchical Modeling, Bayesian Analysis