Anomalies in the detection of change: When changes in sample size are mistaken for changes in proportions

13Citations
Citations of this article
40Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Detecting changes, in performance, sales, markets, risks, social relations, or public opinions, constitutes an important adaptive function. In a sequential paradigm devised to investigate detection of change, every trial provides a sample of binary outcomes (e.g., correct vs. incorrect student responses). Participants have to decide whether the proportion of a focal feature (e.g., correct responses) in the population from which the sample is drawn has decreased, remained constant, or increased. Strong and persistent anomalies in change detection arise when changes in proportional quantities vary orthogonally to changes in absolute sample size. Proportional increases are readily detected and nonchanges are erroneously perceived as increases when absolute sample size increases. Conversely, decreasing sample size facilitates the correct detection of proportional decreases and the erroneous perception of nonchanges as decreases. These anomalies are however confined to experienced samples of elementary raw events from which proportions have to be inferred inductively. They disappear when sample proportions are described as percentages in a normalized probability format. To explain these challenging findings, it is essential to understand the inductive-learning constraints imposed on decisions from experience.

Cite

CITATION STYLE

APA

Fiedler, K., Kareev, Y., Avrahami, J., Beier, S., Kutzner, F., & Hütter, M. (2016). Anomalies in the detection of change: When changes in sample size are mistaken for changes in proportions. Memory and Cognition, 44(1), 143–161. https://doi.org/10.3758/s13421-015-0537-z

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free