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Perceptual estimation of variance in orientation and its dependence on sample size
Descriptive
TypeOfResource
Text
TitleInfo
(ID = T-1)
Title
Perceptual estimation of variance in orientation and its dependence on sample size
Identifier
ETD_2614
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000053348
Language
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(authority = ISO639-2);
(type = code)
eng
Genre
(authority = marcgt)
theses
Subject
(ID = SBJ-1);
(authority = RUETD)
Topic
Psychology
Subject
(ID = SBJ-2);
(authority = ETD-LCSH)
Topic
Sampling (Statistics)
Subject
(ID = SBJ-3);
(authority = ETD-LCSH)
Topic
Analysis of variance
Subject
(ID = SBJ-4);
(authority = ETD-LCSH)
Topic
Psychophysics
Abstract
(type = abstract)
Recent research has shown that participants are very good at perceptually estimating summary statistics of sets of similar objects (e.g., Ariely, 2001; Chong & Treisman, 2003; 2005). While the research has focused on first-order statistics (e.g., the mean size of a set of discs), it is unlikely that a mental representation of the world includes only a list of mean estimates (or expected values) of various attributes. Therefore, a comprehensive theory of perceptual summary statistics would be incomplete without an investigation of the representation of second-order statistics (i.e., variance). Two experiments were conducted to test participants' ability to discriminate samples that differed in orientation variability. Discrimination thresholds and points of subjective equality for displays of oriented triangles were measured in Experiment 1. The results indicated that participants could discriminate variance without bias and that participant sensitivity (measured via relative thresholds, i.e., Weber fractions) was dependent upon sample size but not baseline variance. Experiment 2 investigated whether participants used a simpler second-order statistic, namely, sample range to discriminate dispersion in orientation. The results of Experiment 2 showed that variance was a much better predictor of performance than sample range. Taken together, the experiments suggest that variance information is part of the visual system's representation of scene variables. However, unlike the estimation of first-order statistics, the estimation of variance depends crucially on sample size.
PhysicalDescription
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electronic resource
Extent
iii, 30 p. : ill.
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application/pdf
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text/xml
Note
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M.S.
Note
Includes abstract
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Steven A. Cholewiak
Name
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Cholewiak
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Steven A.
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1984-
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author
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Steven Cholewiak
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(type = family)
Singh
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(type = given)
Manish
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chair
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Advisory Committee
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Manish Singh
Name
(ID = NAME-3);
(type = personal)
NamePart
(type = family)
Feldman
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(type = given)
Jacob
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internal member
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Advisory Committee
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Jacob Feldman
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Kowler
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(type = given)
Eileen
Role
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(authority = RULIB)
internal member
Affiliation
Advisory Committee
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Eileen Kowler
Name
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NamePart
Rutgers University
Role
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degree grantor
Name
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Graduate School - New Brunswick
Role
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(authority = RULIB)
school
OriginInfo
DateCreated
(qualifier = exact)
2010
DateOther
(qualifier = exact);
(type = degree)
2010
Place
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(type = code)
xx
RelatedItem
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
RelatedItem
(type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
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rucore19991600001
Location
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NjNbRU
Identifier
(type = doi)
doi:10.7282/T3M045H0
Genre
(authority = ExL-Esploro)
ETD graduate
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Rights
RightsDeclaration
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(ID = rulibRdec0006)
The author owns the copyright to this work.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
RightsHolder
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(type = personal)
Name
FamilyName
Cholewiak
GivenName
Steven
Role
Copyright Holder
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Type
Permission or license
DateTime
2010-04-14 23:33:21
AssociatedEntity
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(AUTHORITY = rulib)
Role
Copyright holder
Name
Steven Cholewiak
Affiliation
Rutgers University. Graduate School - New Brunswick
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License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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Technical
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ETD
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application/pdf
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application/x-tar
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542720
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