Function estimation: Quantifying individual differences of hand-drawn functions.
Graphical perception is an important part of the scientific endeavour, and the interpretation of graphical information is increasingly important among educated consumers of popular media, who are often presented with graphs of data in support of different policy positions. However, graphs are multid...
| Publicado en: | Memory & Cognition Vol. 53; no. 1; pp. 242 - 262 |
|---|---|
| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Jan2025
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=182537780&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 182537780 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 0090502X MEG jtl: Memory & Cognition issn: 0090502X maglogo: N pubinfo: dt: Jan2025 vid: 53 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 182537780 10.3758/s13421-024-01598-5 ppf: 242 ppct: 20 formats: fmt: – @attributes: type: T – @attributes: type: P size: 2.9MB tig: atl: Function estimation: Quantifying individual differences of hand-drawn functions. aug: au: Little, Daniel R. Shiffrin, Richard M. Laham, Simon M. affil: https://ror.org/01ej9dk98 Melbourne School of Psychological Sciences, The University of Melbourne, 3010, Parkville, VIC, Australia https://ror.org/01kg8sb98 Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA su: Task performance Undergraduates Allied health personnel Students Psychology Statistical models Graphic arts Data analysis Research funding Statistics sug: subj: Task performance Undergraduates Allied health personnel Students Psychology Statistical models Graphic arts Data analysis Research funding Statistics keyword: Gaussian processes Graphical perception Individual differences Gaussian processes Graphical perception Individual differences ab: Graphical perception is an important part of the scientific endeavour, and the interpretation of graphical information is increasingly important among educated consumers of popular media, who are often presented with graphs of data in support of different policy positions. However, graphs are multidimensional and data in graphs are comprised not only of overall global trends but also local perturbations. We presented a novel function estimation task in which scatterplots of noisy data that varied in the number of data points, the scale of the data, and the true generating function were shown to observers. 170 psychology undergraduates with mixed experience of mathematical functions were asked to draw the function that they believe generated the data. Our results indicated not only a general influence of various aspects of the presented graph (e.g., increasing the number of data points results in smoother generated functions) but also clear individual differences, with some observers tending to generate functions that track the local changes in the data and others following global trends in the data. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
|---|