CSIR uses predictive tool to forecast 2024 poll results

Staff Writer
By Staff Writer, ITWeb
Johannesburg, 24 May 2024
South Africans will go to the polls on 29 May.
South Africans will go to the polls on 29 May.

The Council for Scientific and Industrial Research (CSIR) will utilise its election night prediction model for the 2024 national and provincial elections.

South Africans will go to the polls on 29 May, to elect the political party to lead the country in the seventh administration. The 2024 general election has been described as the most contested election in the last 30 years.

In a statement, the CSIR says its prediction model relies on two core principles: the analysis of voter behaviour patterns and the sequence in which voting results are announced on election day.

When combined, these enable the team to group voters or voting districts based on their past voting behaviour, utilising a statistical clustering method, it states.

Says CSIR CEO Dr Thulani Dlamini: “The CSIR’s election prediction model is not a polling system, but a model that uses statistical and mathematical analysis to predict election outcomes.

“It showcases how statistical clustering and some mathematical algorithms can achieve good predictions from a small sample of results. The election prediction model operates on the basis of reducing the bias resulting from the ‘non-randomness’ of the incoming results that arise from the order in which the results are received.”

According to the CSIR, its model was first introduced during the 1999 general election. Since then, it has been employed during the last 10 South African national and municipal elections.

When applied in previous elections, the model typically achieved a high degree of accuracy at a national level once approximately 5% of the results had been tallied, it says.

The CSIR adds that predictions become more stable and accurate as more voting districts are counted, ultimately converging to the final results once all voting districts have been declared.

“The organisation possesses robust capabilities in mathematics and statistics, which are applied to deliver precise results and can be customised for various forms of predictive analysis and forecasting,” concludes Dlamini.