The aim of this study was to investigate students’ achievement in introductory statistics courses taking into account the relationships between cognitive and non-cognitive factors. It was hypothesised that achievement was related to background in mathematics (a cognitive variable), as well as to attitudes toward statistics and anxiety (non-cognitive variables). Students were presented with measures assessing their attitudes, mathematical competence, and anxiety toward courses and examinations at the beginning and at the end of their statistics course. Achievement was assessed by tasks assigned during the course, as well as by students’ final grades and the number of exam failures. The results reveal the relationships between cognitive and non-cognitive factors, their changes during the course, and how both interact in predicting achievement.

This study investigated elementary school teachers’ comprehension of data displays. Assessment, interview, and observation data were analyzed to determine their level of comprehension. Results revealed that the teachers were proficient at “reading the data” and computation types of “reading between the data” questions, but were unsuccessful with questions that assessed higher levels of graphical comprehension. Many of the difficulties exhibited by the teachers appear to be attributable to a lack of exposure to the content. Implications for teacher preparation, professional development, and curricula development are discussed.

There is growing recognition of the importance of developing young students’ informal inferential reasoning (IIR). This focus on informal inference in school statistics has implications for teacher education. This study reports on 26 preservice teachers utilizing Lesson Study to support a focus on the teaching of IIR in primary classrooms. Participants demonstrated proficiency reasoning about the elements fundamental to informal inferential reasoning but had difficulties developing pedagogical contexts to advance primary students’ informal inferential reasoning. Specifically, issues emerged relating to data type, an excessive focus on procedures, locating opportunities for IIR, and a lack of justification and evidence-based reading. Focusing on the lesson as the unit of analysis combined with classroom-based inquiry supported the development of statistical and pedagogical knowledge.