BA (Social Sciences)- Single Major Statistics
Wilson Moseki Thupeng holds a BA (Social Sciences) - Single Major in Statistics (1991), from the University of Botswana and an MSc. in Statistics (1995) from the University of Sheffield in the United Kingdom. He joined the Department of Statistics of as a Staff Development fellow in 1991 and became Lecturer in 1995. He has extensive experience in teaching a variety of courses in probability and statistics and their application.
In the area of research, Mr Thupeng has supervised a number of both undergraduate and postgraduate students working mainly in the area of statistical analysis and modelling of environmental data and financial time series. He takes great interest in these areas since environmental extremes are the greatest threat to humanity and, unusually large fluctuations in financial assets may pose a major risk to investors, leading to huge economic and social losses. He has published a number of papers in these two areas. In addition, he has been assigned the role of Coordinator of the the Department of statistics' Undergraduate Research project course which involves, amongst others, assisting students to apply for research funds and organising seminars for students to present and disseminate results of their research work.
Teaches a wide area of courses in Probability and Statistics ranging from calculus, probability, univariate and multivariate distribution theory, multivariate statistical methods (multivariate data analysis) to Bayesian inference.
Extreme value theory and applications,
Multivariate theory and methods
Applications of statistics to financial time series and environmental data.
Modelling Bivariate Financial Time Series Using Extreme Value Copulas
Modelling extreme meteorological variables using extreme value theory
Modelling volatility of stock returns using GARCH models (On-going)
1. Wilson Moseki Thupeng (2019). STATISTICAL MODELLING OF ANNUAL MAXIMUM RAINFALL FOR BOTSWANA USING EXTREME VALUE THEORY. International Journal of Applied Mathematics & Statistical Sciences (IJAMSS), Vol. 8, Issue 2, pp 1 – 10.
2. K. Thaga, R. Sivasamy And W. M. Thupeng (2017). Arcsine Cumulative Sum Control Chart. International Journal of Statistics: Advances in Theory and Applications Vol. 1, Issue 1, 2017, pp 111-120.
3. W. M. Thupeng, T. Mothupi, B. Mokgweetsi, B. Mashabe & T. Sediadie (2017). 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 Study Of Maun. International Journal of Applied Mathematics & Statistical Sciences (IJAMSS), Vol. 7, Issue 1, pp 1 – 12.
4. Wilson Moseki Thupeng (2016). Use of the Three-parameter Burr XII Distribution for Modelling Ambient Daily Maximum Nitrogen Dioxide Co