Abstract

The novice statistician is a student in school who is beginning their statistical journey and is learning to think statistically. Novices come to the class with little or no previous experience, and any previous experience they may have is likely to be based on fallacy or small-sample inference; for example, my brother had a bad experience with X, therefore X is bad. Novices have likely had limited interaction with specialised statistical terms, and where they are familiar with the term, it is often in the everyday use of the word rather than in the statistical sense. Through experiences at the school level, novices are enculturated into the language of statistics. The novice is the clay to be moulded through experience into an “expert” statistician for whom statistical thinking is commonplace.

Expert statisticians have many years of experience behind them; they have learnt through experience what works and what does not. Expert statisticians can work with vague and often ill-defined problems and seek solutions, knowing when they can infer about a wider universe and when they cannot. Elements of the statistical enquiry cycle that are meticulously adhered to when working with novice statisticians are not seen in the same way by expert statisticians or necessarily with the same importance.

When working with novice statisticians, statistical processes are aligned to pedagogy—the teaching of statistical concepts, thinking, and processes—and may not directly reflect the practice of the expert statistician. Pedagogical considerations are at the forefront of the work with novice statisticians (students) and therefore influence the decisions made around teaching and learning experiences for the novice. Novice statisticians are practising an approximation of the craft of the expert statistician.

In this presentation examples of actions that can be used to support the development of novice statisticians’ statistical thinking and reasoning are presented and discussed. Statistical teaching and learning actions include building experiences faster, modelling thinking and using visual imagery.