Literature DB >> 24749965

Sample size bias in judgments of perceptual averages.

Paul C Price1, Nicole M Kimura1, Andrew R Smith2, Lindsay D Marshall2.   

Abstract

Previous research has shown that people exhibit a sample size bias when judging the average of a set of stimuli on a single dimension. The more stimuli there are in the set, the greater people judge the average to be. This effect has been demonstrated reliably for judgments of the average likelihood that groups of people will experience negative, positive, and neutral events (Price, 2001; Price, Smith, & Lench, 2006) and also for estimates of the mean of sets of numbers (Smith & Price, 2010). The present research focuses on whether this effect is observed for judgments of average on a perceptual dimension. In 5 experiments we show that people's judgments of the average size of the squares in a set increase as the number of squares in the set increases. This effect occurs regardless of whether the squares in each set are presented simultaneously or sequentially; whether the squares in each set are different sizes or all the same size; and whether the response is a rating of size, an estimate of area, or a comparative judgment. These results are consistent with a priming account of the sample size bias, in which the sample size activates a representation of magnitude that directly biases the judgment of average.

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Year:  2014        PMID: 24749965     DOI: 10.1037/a0036576

Source DB:  PubMed          Journal:  J Exp Psychol Learn Mem Cogn        ISSN: 0278-7393            Impact factor:   3.051


  3 in total

1.  Roles of saliency and set size in ensemble averaging.

Authors:  Aleksei U Iakovlev; Igor S Utochkin
Journal:  Atten Percept Psychophys       Date:  2021-04       Impact factor: 2.199

2.  Exaggerated groups: amplification in ensemble coding of temporal and spatial features.

Authors:  Shoko Kanaya; Masamichi J Hayashi; David Whitney
Journal:  Proc Biol Sci       Date:  2018-05-30       Impact factor: 5.349

3.  The development of perceptual averaging: learning what to do, not just how to do it.

Authors:  Pete R Jones; Tessa M Dekker
Journal:  Dev Sci       Date:  2017-08-15
  3 in total

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