2022•Statistics Education Research JournalOpen access

A FRAMEWORK FOR THINKING ABOUT INFORMAL STATISTICAL INFERENCE

Katie Makar, Andee Rubin

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Abstract

Informal inferential reasoning has shown some promise in developing students’ deeper understanding of statistical processes. This paper presents a framework to think about three key principles of informal inference – generalizations ‘beyond the data,’ probabilistic language, and data as evidence. The authors use primary school classroom episodes and excerpts of interviews with the teachers to illustrate the framework and reiterate the importance of embedding statistical learning within the context of statistical inquiry. Implications for the teaching of more powerful statistical concepts at the primary school level are discussed. First published May 2009 at Statistics Education Research Journal: Archives

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Informal inferential reasoning has shown some promise in developing students’ deeper understanding of statistical processes. This paper presents a framework to think about three key principles of informal inference – generalizations ‘beyond the data,’ probabilistic language, and data as evidence. The authors use primary school classroom episodes and excerpts of interviews with the teachers to illustrate the framework and reiterate the importance of embedding statistical learning within the context of statistical inquiry. Implications for the teaching of more powerful statistical concepts at the primary school level are discussed. First published May 2009 at Statistics Education Research Journal: Archives

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Available abstract

Informal inferential reasoning has shown some promise in developing students’ deeper understanding of statistical processes. This paper presents a framework to think about three key principles of informal inference – generalizations ‘beyond the data,’ probabilistic language, and data as evidence. The authors use primary school classroom episodes and excerpts of interviews with the teachers to illustrate the framework and reiterate the importance of embedding statistical learning within the context of statistical inquiry. Implications for the teaching of more powerful statistical concepts at the primary school level are discussed. First published May 2009 at Statistics Education Research Journal: Archives

Key concepts: Statistical inference, Statistical thinking, Mathematics education, Context (archaeology), Inference, Statistical model, Probabilistic logic, Key (lock)

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