A large collection of estimation phenomena (e.g. biases arising when adults or children estimate remembered locations of objects in bounded spaces; Huttenlocher, Newcombe & Sandberg, 1994) are commonly explained in terms of complex Bayesian models. We 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 could be explained in terms of a simple psychophysical model of proportion estimation. Moreover, some individual data were not compatible with the requirements of the more complex Bayesian model.
Hilary Barth, Ellen Lesser, Jessica Taggart, and Emily Slusser. "Spatial estimation: a non-Bayesian alternative" Faculty Publications (2015).
This is the peer reviewed version of the following article: Barth, H., Lesser, E., Taggart, J. and Slusser, E. (2015), Spatial estimation: a non-Bayesian alternative. Developmental Science, 18: 853–862. doi: 10.1111/desc.12264, which has been published in final form at http://dx.doi.org/10.1111/desc.12264. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.