ABSTRACT
This chapter discusses individual differences include working memory capacity; learning, including perceptual and language learning; and multitasking ability. The capacity coefficients developed by Townsend and various colleagues are particularly well suited to quantifying individual-level efficiency of combining multiple sources of information. The chapter reviews each part of this approach: first, the capacity coefficients; second, fPCA applied to capacity coefficients; and third, hierarchical and k-means clustering. One of Townsend's pioneering contributions in mathematical psychology is the use of hazard functions as the basic tool for making inferences about information processing capacity. Statistical learning, a term often used interchangeably with machine learning, refers to the process of detecting and leveraging structure in multivariate data. Johnson, Blaha, Houpt, and Townsend used Systems Factorial Technology methodologies to study the information processing architecture and efficiency of hierarchical form perception in adolescents with adolescents. Hierarchical clustering to uncover individual differences in the influence of stereo depth cues on the capacity of visual search.
