Learning to reason from samples

Abstract

The goal of this article is to introduce the topic of learning to reason from samples, which is the focus of this special issue of Educational Studies in Mathematics on statistical reasoning. Samples are data sets, taken from some wider universe (e.g., a population or a process) using a particular procedure (e.g., random sampling) in order to be able to make generalizations about this wider universe with a particular level of confidence. Sampling is hence a key factor in making reliable statistical inferences. We first introduce the theme and the key questions this special issue addresses. Then, we provide a brief literature review on reasoning about samples and sampling. This review sets the grounds for the introduction of the five articles and the concluding reflective discussion. We close by commenting on the ways to support the development of students’ statistical reasoning on samples and sampling.