Author(s)

A. K. M. Raquibul Bashar¹, Chris P. Tsokos²

¹Department of Mathematics & Computer Science, Augustana College, Rock Island, IL, USA.
²Department of Mathematics & Statistics, University of South Florida, Tampa, FL, USA.

In this study, we utilized data from Transparency International (TI) on 175 countries and from the World Bank (WB) on over 200 countries to develop the Worldwide Governance Indicators (WGI), which cover six dimensions of governance: 1) Voice and Accountability, 2) Political Stability, 3) Government Effectiveness, 4) Regulatory Quality, 5) Rule of Law, and 6) Control of Corruption. We identified and verified the statistical significance of the probability distribution function (PDF) for the Corruption Perception Index (CPI) scores. This PDF allows us to probabilistically characterize CPI score behavior and determine the likelihood of different score ranges, making it a valuable tool for unsupervised clustering and supervised classification that can be implemented in the domain of Artificial Intelligence of studying issues in social science.

CPI (Corruption Perception Index), WGI (World Governance Indicator), PDF (Probability Distribution Function), CDF (Cumulative Distribution Function), GOF (Goodness-of-Fit)

Bashar, A. K. M. R., & Tsokos, C. P.(2024) Parametric and Statistical Analysis on Corruption Perception Index (CPI) of Countries of the World Based on World Governance Index (WGI) Data of Transparency International (TI). Open Journal of Social Sciences, 12, 396-416. doi: 10.4236/jss.2024.129023.