The workshop is on Day 1 and is included in the conference registration.

Risky Statistical Business: Asking questions upfront to bypass risks of statistical advising

Sama Low-Choy

For statisticians of any level of experience, statistical advising can be immensely satisfying, yet also, at times, present a minefield of risky possibilities. The business, politics and interpersonal relations can be subject to many pressures, unknowns, and diversity of problems. To complicate matters, those who are relatively new to advising (albeit with experience in teaching or research) may be unprepared for these challenges.

For the past seven years, Sama Low-Choy has been mentoring early career research methods advisors (RMAs). Their role is to advise researchers (either within or across academic groups) who are struggling with methods that are new to them — where methods may be statistical, mixed (qualitative and quantitative), data science or modelling. To help support these GU RMAs she has developed a questionnaire which helps guides their initial consults, to learn about researchers asking for assistance, and their research problems and context.

These questions have evolved over varied experience as a statistical advisor, teacher and collaborative researcher in universities, government and briefly in industry. The delivery of questions is flexible. As an experienced advisor, She elicit answers via an unstructured process, so the protocol serves as a checklist. However early career advisors may adopt a semi- structured interview and/or online questionnaire format. In this workshop she will work through a few questions, with anecdotes of how they work in real life. In particular, she will highlight the hidden power of these questions, to help manage or bypass risky situations, before they can occur.

Intended Audience

This workshop may be of interest to statistical advisors of any level, wishing to consider how initial consults can be approached to help reduce risks. She welcomes input on the questions proposed and their intended effects to manage some risks.


Think of 1–3 unfortunate situations (or near-misses) that you, your colleagues or peers have encountered, during statistical advising or consulting. Alternatively think of hypothetical situations that you are concerned may occur. You may wish to share these examples during activities designed to help you explore questions and their role in protecting all involved.

About the Presenter

Most of Sama’s career has had a heavy emphasis on statistical advising and/or consulting. She has accrued nearly two decades in academic contexts. These bookended seven years in Government and three years in a CRC (cooperative research centre) where her role included building capacity for statistics in the respective organisations. Her consultancy skills were minted in the melting pot as a very junior member of a team supporting an expert witness in a court case.

Her next role mixed consultancy and research methods advising (RMA) in a team of 3-5 consultants, who developed their own processes and risk management. Working in Government required strict attention to process, legalities and regulation, whilst also enabling her to identify problems from the “inside”. To support her position as a sole statistician she retained links to academia through collaborative projects and mentoring undergraduate students on industry projects. In 2004 she attended three separate one-week workshops that re-ignited her passion for research, triggering a sideways move back into academia with successive periods dedicated to statistical consulting, postdoctoral research, collaborative research or teaching. Now, a Senior Statistician at Griffith University, she continues to work on building researchers’ capacity for quantitative research methods, with a balanced workload of advising, teaching, collaborative research and service. This has seen a subtle shift to support researchers within an Academy predominantly focusing on social, behavioural and environmental questions, with a strong tradition for qualitative including descriptive research methods.