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 henceakeyfactorinmakingreliablestatisticalinferences.Wefirstintroducethethemeandthe 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 thefivearticlesandtheconcludingreflectivediscussion.Weclosebycommentingontheways to support the development of students’ statistical reasoning on samples and sampling.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education