A Framework for Thinking about Informal Statistical Inference


Authors: 
Katie Makar and Andee Rubin
Volume: 
8(1)
Pages: 
online
Year: 
2009
Publisher: 
Statistics Education Research Journal
URL: 
http://www.stat.auckland.ac.nz/~iase/publications.php?show=serjarchive
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.

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

register