Open AccessSample size weighting follows a curvilinear function.
Author(s) -
Natalie A. Obrecht
Publication year - 2019
Publication title -
journal of experimental psychology. learning, memory, and cognition
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.758
H-Index - 156
eISSN - 1939-1285
pISSN - 0278-7393
DOI - 10.1037/xlm0000615
Subject(s) - sample size determination , sample (material) , weighting , curvilinear coordinates , statistics , normative , mathematics , psycinfo , econometrics , function (biology) , psychology , geometry , physics , chemistry , medline , evolutionary biology , biology , acoustics , thermodynamics , philosophy , biochemistry , epistemology
Previous research is mixed regarding whether laypeople are sensitive to sample size. Here the author argues that this is in part because sample size sensitivity follows a curvilinear function with decreasing sensitivity as sample size become larger. This functional form reconciles apparent discrepancies in the literature, accounting for results where sample size is greatly attended to or nearly overlooked. The curvilinear form is found across confidence and estimation tasks that have square-root and linear normative standards. Thus, although people intuitively know that larger samples provide more reliable information, they do not modulate how they weight sample size in different circumstances. Further, individuals higher in numeracy show greater sensitivity to sample size than those lower numeracy (i.e., have a steeper curvilinear slope), but still underweight it relative to normative standards. Providing raw data can boost sample size use for individuals who are lower in numerical ability. (PsycINFO Database Record (c) 2019 APA, all rights reserved).