STUDENTS’ EMERGENT ARTICULATIONS OF STATISTICAL MODELS AND MODELING IN MAKING INFORMAL STATISTICAL INFERENCES
Hana Manor Braham, Dani Ben‐Zvi
Abstract
Hana Manor Braham, Dani Ben‐Zvi
Abstract
A fundamental aspect of statistical inference is representation of real-world data using statistical models. This article analyzes students’ articulations of statistical models and modeling during their first steps in making informal statistical inferences. An integrated modeling approach (IMA) was designed and implemented to help students understand the relationship between sample and population, as well as reasoning with models and modeling. We explore the articulations of a pair of primary school students, who had previously participated in the Connections Project exploratory data analysis (EDA) activities, and suggest an emergent conceptual framework for reasoning with statistical models and modeling. We shed light on ideas of statistical models and modeling that can emerge among primary students and how they articulate those ideas. Implications for teaching and research are discussed. First published November 2017 at Statistics Education Research Journal Archives
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A fundamental aspect of statistical inference is representation of real-world data using statistical models. This article analyzes students’ articulations of statistical models and modeling during their first steps in making informal statistical inferences. An integrated modeling approach (IMA) was designed and implemented to help students understand the relationship between sample and population, as well as reasoning with models and modeling. We explore the articulations of a pair of primary school students, who had previously participated in the Connections Project exploratory data analysis (EDA) activities, and suggest an emergent conceptual framework for reasoning with statistical models and modeling. We shed light on ideas of statistical models and modeling that can emerge among primary students and how they articulate those ideas. Implications for teaching and research are discussed. First published November 2017 at Statistics Education Research Journal Archives
Key concepts: Statistical inference, Statistical model, Representation (politics), Mathematics education, Inference, Computer science, Sample (material), Scientific modelling