Spatial estimation: a non-Bayesian alternative
Hilary C. Barth, Ellen Lesser, Jessica Taggart, Emily B. Slusser · 2016
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.