Abstract
AbstractThe goal of this article is to introduce the topic oflearning to reason from samples, which is the focus of this special issue of Educational Studies in Mathematics onstatistical 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.
Highlights
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
Looking at distributions of sample means for many samples drawn from a single population allows us to see how one sample compares to the rest of the samples, leading us to determine if a sample is surprising or not surprising
Comparing means of samples drawn from the same population helps build the idea of sampling variability, which leads to the notion of sampling error, a fundamental component of statistical inference whether constructing confidence intervals or testing hypotheses
Summary
The pervasiveness of data in everyday life is a global trend. People are encircled by statistics in their everyday life and must become savvy consumers of data (Watson, 2002). Looking at distributions of sample means for many samples drawn from a single population allows us to see how one sample compares to the rest of the samples, leading us to determine if a sample is surprising (unlikely) or not surprising This is an informal precursor to the more formal notion of p value that comes with studying statistical inference (Garfield & Ben-Zvi, 2008). A group of researchers have come to focus on sample and sampling as being at the heart of statistical inference and relevant at all levels of schooling, even in the early years This special issue of Educational Studies in Mathematics aims at presenting state-of-the-art studies on students’ understanding of samples and sampling when making informal statistical inferences. & What are innovative and effective approaches, tasks, tools, or sequences of instructional activities that may be used to promote students’ understanding of reasoning about samples and sampling in making statistical inferences?
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