Model-based Informal Inference

Abstract

Following recent scholarly interest in teaching informal linear regression models, this study looks at teachers' reasoning about informal lines of best fit and their role in pedagogy. The case results presented in this journal paper provide insights into the reasoning used when developing a simple informal linear model to best fit the available data. This study also suggests potential in specific aspects of bidirectional modelling to help foster the development of robust knowledge of the logic of inference for those investigating and coordinating relations between models developed during modelling exercises and informal inferences based on these models. These insights can inform refinement of instructional practices using simple linear models to support students' learning of statistical inference, both formal and informal.

Algebraization Levels in the Study of Probability

“…Today we are witnessing a debate in statistics education regarding the possibility of teaching different contents, such as statistical inference to students with limited knowledge of algebra or calculus through informal approaches [1][2][3]. A similar discussion is observed in relation to other mathematical topics, for which the recommendation is a stronger emphasis on understanding and solving problems [4] while avoiding unnecessary formalizations as well as learning computational algorithms, which are less relevant because of technology.…”