Guiding RUbric

In addition to this network of Statistics Supervisors, the core group developed a guiding rubric as a solution to support active early-career supervisors in South Africa, particularly in the absence of senior mentorship. This proposed guiding rubric is intended for supervisors and students within statistical sciences, but this can be applied in a wide range of fields, including, but not be limited to applied and mathematical statistics, data science, machine learning, operations research, biostatistics or biometry, business statistics, econometrics, and psychometrics, as long as the foundation of the research is statistical in nature. The guidelines presented in this rubric are not a prescriptive set of rules, but rather a dynamic document encouraging the growth of both the novice supervisor and the doctoral candidate.

Through this initiative, it is the hope that a novice doctoral supervisor in Statistical Sciences will be more effective in graduating a doctoral candidate, as well as providing a more holistic and understandable journey for the student, hopefully initiating their movement into academia. This initiative will therefore result in 

1. effective emerging doctoral supervisors in Statistical Sciences; 

2. faster doctoral student graduations; 

3. more enlightened doctoral student graduates. 

A current version of this guiding rubric is given below or can be accessed here (download to use).