The Department of Applied Mathematics and Statistics offers a diverse portfolio of undergraduate and postgraduate programmes, namely BSc Actuarial Science, BSc Applied Mathematics and Computational Sciences BSc Applied Statistics, and MSc Biostatistics and Epidemiology. The department is committed to providing rigorous training in quantitative analysis, modelling, and data-driven decision-making to meet academic, professional, and societal needs.

The department is supported by a dedicated and multidisciplinary academic staff with expertise in actuarial science, applied mathematics, statistics, biostatistics, epidemiology, and computational methods. Staff members are actively engaged in teaching, research, and community service, ensuring high-quality instruction aligned with international standards and professional bodies.

Through its programmes, the department aims to produce graduates equipped with strong analytical skills, practical competence, and the ability to address complex real-world problems across finance, health, industry, and policy.

• Vision Statement
  To be a leading  centre of excellence in Mathematical  Sciences, advancing innovative data driven research and solutions that  advance national development and industrial transformation.
•     Mission Statement
  
  To cultivate a vibrant academic environment that nurtures critical thinking, interdisciplinary collaboration, and applied research in mathematical sciences, empowering graduates and researchers to contribute to the industrialisation and modernisation of society through innovative, data-driven solutions.

The Department of Applied Mathematics and Statistics is committed to advancing knowledge and fostering innovation through:

1. Teaching that cultivates analytical, computational, and problem-solving skills relevant to modern scientific, technological, and industrial needs.
2. Research that generates impactful solutions to real-world challenges in health, agriculture, environment, and industry.
3. Community Service that empowers local communities through data literacy, mathematical modelling, and capacity-building initiatives.
4. Innovation that drives the creation of mathematical and statistical tools, software, and models that support evidence-based decision-making and entrepreneurship.
5. Industrialisation through strategic partnerships and applied research that transform mathematical and statistical expertise into practical technologies and sustainable enterprises.