While correlated data methods (like random effect models and generalized estimating equations) are commonly applied in practice, students may struggle with understanding the reasons that standard regression techniques fail if applied to correlated outcomes. To this end, this article presents an in-class activity using results from Monte Carlo…

The Dodgson winner seems very intuitive and reasonable: when a Condorcet winner doesn't exist, pick the candidate that is closest, under some measure, to being a Condorcet winner. However, Dodgson's method is computationally intensive. Approximate methods are more tractable. By placing these methods in a geometric framework, we can understand how…

Narrow Window theory, suggested by Y. Kareev ten years ago, has so far focused on one central implication of the limited capacity of working memory on intuitive correlation estimation, namely, overestimation of the distal population correlation. This paper points to additional and perhaps more dramatic implications due to the large dispersion of…