August 2012
Volume 12, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2012
Does variability affect statistical averaging of length and orientation?
Author Affiliations
  • Jesse Moyer
    Psychology, University of South Carolina
  • Anne Payne
    Psychology, University of South Carolina
  • C. Holley Pitts
    Psychology, University of South Carolina
  • Melanie Palomares
    Psychology, University of South Carolina
Journal of Vision August 2012, Vol.12, 351. doi:https://doi.org/10.1167/12.9.351
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Jesse Moyer, Anne Payne, C. Holley Pitts, Melanie Palomares; Does variability affect statistical averaging of length and orientation?. Journal of Vision 2012;12(9):351. https://doi.org/10.1167/12.9.351.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Limited attention capacities necessitate statistical summary representations such as statistical averaging. We examined how statistical averaging might be affected by feature type and variability in the set. Do we average length and orientation in a similar way? How similar should the items be in order to be averaged? Participants were presented shown sets of lines (n = 2, 3, 4, 9) for 133 ms. In Expts. 1-2, participants were asked to identify the length that represented the average or a member of the set. The lines were uniformly vertical in Expt. 1 and were randomly oriented (between -75 and +75 deg) in Expt. 2. In Expts. 3-4, participants were asked to identify the orientation that represented the average or a member of the set. The lines were all 2.7 deg in Expt. 3, and had randomly selected lengths (between 1.0 and 2.33 deg) in Expt. 4. Across all four experiments, we found that accuracy for identifying a set’s average feature, either length or orientation, was higher than the accuracy for identifying a member feature. Adding variability to the set in a feature dimension irrelevant to the task did not affect the pattern of accuracies. These data suggest that statistical averaging is robust even in sets with heterogeneous members.

Meeting abstract presented at VSS 2012

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×