The Citizen (KZN)

From data to insights


- Inger Fabris-Rotelli, Ansie Smit, Danielle Jade Roberts, Daniel Maposa, Fabio Mathias Correa, Michael Johan von Maltitz and Sonali Das

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

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