Mathematical Statistics

Statistics is the science that makes sense of quantitative information. Statisticians describe and analyse data, using mathematical statistical and probability models. Based on these analyses, conclusions and calculated decisions can be made under uncertainty.

Students who study Statistics acquire analytical skills for scientific decision making in business and industry. After successfully completing their studies and gaining sufficient practical experience, they have the opportunity of obtaining the professional qualifications of chartered or certificated statistician.

Statistics is a truly interdisciplinary science that is used in areas as diverse as:

  • Health and medicine, e.g. in designing the clinical trials of a new pharmaceutical  drug;
  • Business, e.g. calculating consumer demand for a new product or optimising the investment yield of portfolios;
  • Government, e.g. analysing census and crime data;
  • Environment/agriculture, e.g. extrapolating rhino population figures;
  • Industry, e.g. designing experiments and optimising processes.

For this reason, statisticians are highly sought after in business, industry, research and public sectors where they take up roles as data mining experts, data managers, statistical analysts and business analysts. Qualified students can look forward to an exciting and financially rewarding career, often working alongside management and decision-makers in major organisations.

The mathematical statistics programme is more theoretical in nature and focusses more on the underlying mathematical theory of the statistical techniques.

Undergraduate

POSTgraduate

Special registration for honours and masters modules

Students who wish to register for any of these post graduate modules as part of a degree offered outside the Department of Statistics and Actuarial Science, need to formally apply to the department for the module(s) by:

  • Send personal / contact details;
  • The module(s) you wish to apply for, as well as the degree you will be registered for, to hrandall@sun.ac.za & slubbe@sun.ac.za;
  • Attach a complete study record to your e-mail;
  • Make sure of the pre-requisites of the modules you wish to apply for, specifically regarding the R block module which takes place roughly two weeks before normal lecturing starts.
  • Closing date for applications is 30 January each year (and 20 January for 13074-723 Introduction to R).