Hilary Barth, associate professor of psychology, is the co-author of an article titled “Spatial Estimation: A Non-Bayesian Alternative,” published in Developmental Science, Volume 18, pages 853-862, in 2015. The paper is co-authored by Ellen Lesser ’15, as well as former Cognitive Development Labs coordinator Jessica Taggart and former postdoctoral fellow Emily Slusser.
A large collection of estimation phenomena (for example, biases arising when adults or children estimate remembered locations of objects in bounded spaces) are commonly explained in terms of complex Bayesian models. Bayesian cognitive models seek to model human mental processes as approximations to ideal statistical inference.
In this study, Barth and her co-authors provide evidence that some of these phenomena may be modeled instead by a simpler non-Bayesian alternative.
Undergraduates and 9- to 10-year-olds completed a speeded linear position estimation task. Bias in both groups’ estimates, they suggest, could be explained in terms of a simple psychophysical model of proportion estimation.