The ability to analyse qualitative information from quantitative information, and/or to create<br>new information from qualitative and quantitative information is the key task of statistical literacy in the<br>21st century. Although several studies have focussed on critical evaluation of statistical information, this<br>aspect of research has not been clearly conceptualised as yet. This paper presents a hierarchy of the<br>graphical interpretation component of statistical literacy. 175 participants from different educational levels<br>(junior high school to graduate students) responded to a questionnaire and some of them were also<br>interviewed. The SOLO Taxonomy was used for coding the students' responses and the Rasch model was<br>used to clarify the construction of the hierarchy. Five different levels of interpretations of graphs were<br>identified: Idiosyncratic, Basic graph reading, Rational/Literal, Critical, and Hypothesising and Modelling.<br>These results will provide guidelines for teaching statistical literacy.
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