Statistical inference involves drawing scientifically-based conclusions describing natural processes or observable phenomena from datasets with intrinsic random variation. We designed, implemented, and validated a new portable randomization-based statistical inference infrastructure (http://socr.umich.edu/HTML5/Resampling_Webapp) that blends…

In two experiments, participants made inferences from weather maps, before and after they received instruction about relevant meteorological principles. Different versions of the maps showed either task-relevant information alone, or both task-relevant and task-irrelevant information. Participants improved on the inference task after instruction,…

We apply instrumental variables (IV) techniques to a pooled data set of employment-focused experiments to examine the relation between type of preschool childcare and subsequent externalizing problem behavior for a large sample of low-income children. To assess the potential usefulness of this approach for addressing biases that can confound…

Regardless of the related discipline, students in statistics courses invariably have difficulty understanding the connection between the numerical values calculated for end-of-the-chapter exercises and their usefulness in decision making. This disconnect is, in part, due to the lack of time and opportunity to actually design the experiments and…