This article introduces a collection of four datasets, similar to Anscombe's quartet, that aim to highlight the challenges involved when estimating causal effects. Each of the four datasets is generated based on a distinct causal mechanism: the first involves a collider, the second involves a confounder, the third involves a mediator, and the…

This report characterizes forms of dialogic support that a sixth-grade teacher generated during whole-class and small-group conversations to help students develop a practice of statistical modeling. During four weeks of instruction, students constructed and revised models to account for variability and uncertainty across a variety of random…

Using software to teach statistical inference in introductory courses opens the door for methods and practices that are more conceptually appealing to students. With an increasing number of fields requiring competency in statistics including data science, natural and social sciences, public health and more, it is crucial that we as instructors…

Most current statistics courses include some instruction relevant to causal inference. Whether this instruction is incorporated as material on randomized experiments or as an interpretation of associations measured by correlation or regression coefficients, the way in which this material is presented may have important implications for…

Recent research suggests the benefits of supporting a progressive understanding of concepts of inference prior to the teaching of procedures and formal calculations through the study of informal statistical inference (ISI). To contribute to the growing knowledge about the early learning and teaching of statistics, particularly regarding the…

Data Analytics has grown dramatically in importance and in the level of business deployments in recent years. It is used across most functional areas and applications, some of the latter including market campaigns, detecting fraud, determining credit, identifying assembly line defects, health services and many others. Indeed, the realm of…

This study contributes to the call for influencing practice by increasing attention to how learning environments can be designed to support learning in statistical inference. We report on a design experiment in secondary school (students 14-16 years old), that resulted in a set of lessons with the learning goal of teaching students how to apply…

An online authentic learning environment (OnALE) is proposed in this study to facilitate students' learning of inferential statistics in a real-life context. The efficacy of the OnALE, in comparison to the conventional approach relative to the students' performance, was explored. Respondents from the experimental group were purposively selected to…

As a foundational approach in inferential statistics, hypothesis testing (HT) is considered as one of the most challenging topics for teaching and learning. A promising approach is through the consideration of students' learning modalities, as demonstrated in vast applications; however, contentions that surround the use of learning modality in…

Most current statistics courses include some instruction relevant to causal inference. Whether this instruction is incorporated as material on randomized experiments or as an interpretation of associations measured by correlation or regression coefficients, the way in which this material is presented may have important implications for…

Growing scholarship on the pedagogical applications of statistical modeling is currently taking place to create adaptations of this practice to introduce novices to statistics. These are intended to promote novices' reasoning, and are typically void of formal mathematical procedures and calculations. In this article, we define the potential…

Data modeling is an essential activity in a data-driven society, but such a topic and how the context shapes it has received limited attention. This paper reports on research that investigated the role of context in supporting early statistical reasoning in the data modeling process. The data were collected throughout sessions in which young…

The advent of data science has led to statistics education researchers re-thinking and expanding their ideas about tools for teaching statistical modeling, such as the use of code-driven tools at the secondary school level. Methods for statistical inference, such as the randomization test, are typically taught within secondary school classrooms…

Employing a statistical modeling inspired pedagogy is becoming a widespread practice in the statistics education community. Many have incorporated the practice of formulating conjectures in their modeling-enhanced educational designs and have reported on its benefits. We further elucidate the mechanism through which students' conjecturing may be…

Statistical association is a key facet of statistical literacy: claims based on relationships between variables or ideas rooted in data are found everywhere in media and discourse. A key development in introductory statistics curricula is the use of simulation-based inference, which has shown positive outcomes for students, especially in regards…