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2016: Master of Arts in Statistics, 4844³ÉÈËÃâ·Ñ¸£Àû

2008: Bachelor of Science Degree in Statistics, 4844³ÉÈËÃâ·Ñ¸£Àû

2006: Diploma in Statistics, 4844³ÉÈËÃâ·Ñ¸£Àû

Boikanyo Mokgweetsi is currently a lecturer at the 4844³ÉÈËÃâ·Ñ¸£Àû in the Department of Statistics. He is educated at the 4844³ÉÈËÃâ·Ñ¸£Àû with Diploma in Statistics, BSc Degree in Statistics, and MA in Statistics. He has been at the 4844³ÉÈËÃâ·Ñ¸£Àû since 2013 where he rose through the ranks from a Staff Development Fellow to Lecturer position.

His research Interest Include Bayesian inference and Applications, machine learning/Artificial Neural Networks, and Spatial Statistics. Mr. Boikanyo Mokgweetsi is involved with many professional service activities within and outside the 4844³ÉÈËÃâ·Ñ¸£Àû.

•Statistical Distributions

•Statistical Modelling and Applications

•Probability

•Mathematics for Business and Social Sciences

•Statistical Computing

Computer Literacy and Familiarity
Microsoft Office (Word, Excel, PowerPoint) • R Software • SPSS • LaTex Software • WinBUGS Software • BayesX Software • Stan Software • Python

• Bayesian inference

• Development and Application of Bayesian inference Methods in HIV/TB research

• Actuarial science methods and applications to non-life insurance

• Bayesian machine learning/Artificial Neural Networks in Disease Mapping

• Spatial Statistics

• Statistics for Real Estate Valuation

• Ntseane, D. M., Ali, J., Hallez, K., Mokgweetsi, B., Kasule, M., & Kass, N. E. (2020). The features and qualities of online training modules in research ethics: a case study evaluating their institutional application for the 4844³ÉÈËÃâ·Ñ¸£Àû. Global Bioethics, 31(1), 133-154.

• Thupeng, W. M., Mokgweetsi, B., & Mothupi, T. (2019). Posterior Predictive Checks for the Generalized Pareto Distribution Based on a Dirichlet Process Prior. American Journal of Theoretical and Applied Statistics, 8(6), 287-295.

•Thupeng, W. M., Mothupi, T., Mokgweetsi, B., Mashabe, B., & Sediadie, T. (2018). A Principal Component Regression Model, for Forecasting Daily Peak Ambient Ground Level Ozone Concentrations, in the Presence of Multicollinearity Amongst Precursor Air Pollutants and Local Meteorological Conditions: A Case 4844³ÉÈËÃâ·Ñ¸£Àû of Maun. International Journal of Applied Mathematics & Statistical Sciences ( IJAMSS ), 7(1). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3128175