Statistics forms the backbone of data-driven decision making, providing tools to collect, analyze, and interpret complex information and At UKZN provides rigorous training in the mathematical foundations of data analysis, with emphasis on probability theory, statistical inference, and experimental design. Students develop expertise in both classical and modern statistical methodologies, learning to apply these techniques to solve real-world problems across scientific, industrial and social domains. The programme emphasizes computational statistics using industry-standard tools like R and SAS, while maintaining strong theoretical foundations. Graduates are prepared for careers in research institutions, government agencies, and industries requiring advanced analytical capabilities, particularly in South Africa’s growing data-driven sectors.
Statistics includes Data Science, a sub-discipline that involves analyzing large datasets using statistical, computational, and machine learning methods.
UKZN’s Data Science sub-discipline focuses on extracting knowledge and insights from complex, large-scale datasets through computational and statistical methods. The curriculum combines machine learning, big data technologies, and domain-specific applications to address contemporary challenges in fields like healthcare, finance, and environmental science. Students gain hands-on experience with cutting-edge tools and platforms while developing the programming and analytical skills demanded by today’s data-intensive industries. The programme prepares graduates for diverse roles in business intelligence, predictive analytics, and artificial intelligence development, with particular relevance to South Africa’s digital transformation needs.
Why Study Statistics at UKZN?
The Statistics programme at UKZN develops strong quantitative skills through:
Rigorous training in statistical theory and applied methods
Specialized software instruction (R, SAS, Python)
Applications to South African priorities:
Health statistics
Economic modeling
Environmental data analysis
(For detailed module information, please consult our current College Handbook)
This three-year undergraduate course leads to the degree of Bachelor of Science (BSc) in the M stream, which encompasses programmes/ majors within the disciplines of Computer Science, Mathematics, Physics and Statistics.
A one-year specialist programme leading to the degree of Bachelor of Science (Honours). A minimum of 50% must be achieved at BSc level to gain admittance to Honours.
Honours programmes in Statistics (PMB & WVL) are offered.
A Master of Science programme is offered, whereby students engage in research under the supervision of an academic staff member. A minimum of a BSc Honours degree or equivalent must be achieved to be considered for this programme. This is typically two years of full time study.
A Doctor of Philosophy programme is offered where students engage in novel research supervised by academic members of staff. This is typically three years of full-time study and normally follows on from a Master of Science Degree.
This three-year undergraduate course leads to the degree of Bachelor of Science (BSc) in the M stream, which encompasses programmes/ majors within the disciplines of Computer Science, Mathematics, Physics and Statistics. Possible major subject combinations include any two of the following:
NSC degree pass with Maths Level 5 (60%), English and Life Orientation Level 4 (50%) and either Agricultural Science or Life Sciences or Physical Science Level 4 (50%)
30 – 48
CASSE provides alternative access to students predominantly from disadvantaged educational backgrounds who do not meet the entry requirements to enrol for various science and engineering programmes. Though students are expected to study and pass augmented modules in the first two years, they eventually graduate with various qualifications in the school with mainstream students.
NSC degree pass with English and Life Orientation at Level 4 (50%), Maths at Level 3 (40%) and Agricultural Science, Physical Science or Life Sciences at Level 3 (40%)
26 – 48
To apply, please visit our School’s Undergraduate or Postgraduate page for step-by-step instructions, downloadable application forms, and the online application link.
We are a research-led institution, producing knowledge for the rapidly-changing and information-rich world.
UKZN Research Space was developed to increase the visibility, availability and impact of tour students’ research output.
Teachers4DataAnalytics was conceptualized by Prof Delia North (Statistician, UKZN), as a key project to create awareness amongst high school learners of the job opportunities that exist for those that study Data Analytics (Data Science, Statistics) at tertiary level. The project aims to advocate for teachers to appreciate the value of sound statistical reasoning, through fun activities and inspirational talks.
Academic Leader (Acting)
robertsd@ukzn.ac.za | 031 260 1015
