From data to insights

LACK: SA NEEDS ACADEMIC STATISTICIANS

In today’s tech-driven world, data is only useful if it can be collected and explained by experts.

Our world is awash with data. But it is only useful if it can be collected, analysed and explained by experts. That’s where statisticians come in. Both “data scientist” and “statistics lecturer” feature on the government’s critical skills list. Due to the large increase in data available, skilled analysts are needed more than ever before.

We are a group of academic statisticians from South African universities who have compiled a discussion paper to address these issues. We have identified the factors contributing to the capacity crisis in academic statistics. We’ve also proposed a way to improve the quality and quantity of, primarily, doctoral candidates in the various statistical fields.

What’s in a name?

There are many “statistical” fields in academia. Over the years, a divide has emerged between those who research and lecture in applied statistics and their counterparts in mathematical or theoretical statistics.

It is time for statisticians to put aside their disciplinary differences and identify commonalities in their fields. In this way, academic statisticians can come together to build a network of expertise that can support the development of young academics across these imagined divisions.

We also identified the need to standardise assessment across statistics PhDs in SA. Every university sets its own criteria and there may be concerns that standardising assessment for what is essentially creative output may be too prescriptive.

We believe a semi-flexible assessment rubric is vital. This will help to develop high-quality doctoral graduates. It will also guide early-career supervisors to develop the correct goals for their students.

Supervisor-student relationship

Another gap exists in how PhD candidates and their supervisors are supported and mentored. Without sufficient mentoring, early-career supervisors may not know how to nurture a healthy supervisor-student relationship.

They may be unaware of the intricacies inherent in this relationship, let alone the skills they should be imparting to their students.

Now that we have identified critical topics, we have set up a guiding rubric for early-career supervisors in statistics, in consultation with senior supervisors, young academics and industry statisticians. To our knowledge, it is the first of its kind in the field of academic statistics.

It is not designed to be prescriptive. It will be a guide that includes criteria for every area identified as being important to the development of a new researcher.

Fabris-Rotelli, academic – statistician, University of Pretoria; Smit, senior lecturer, University of Pretoria; Roberts, senior lecturer, University of KwaZulu-Natal; Maposa, associate professor of statistics & head of department , University of Limpopo; Correa, associate professor, University of the Free State; von Maltitz, associate professor, mathematical statistics and actuarial science, University of the Free State, and Das, full professor, University of Pretoria

This article is republished from The Conversation