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Statistical Decision Theory Models of Sequential Multiple Observations by Human Observers

dc.contributor.advisorKinchla, R.A.en_US
dc.contributor.authorTheodor, Henry Leonarden_US
dc.contributor.departmentPsychologyen_US
dc.date.accessioned2014-06-18T17:01:39Z
dc.date.available2014-06-18T17:01:39Z
dc.date.created2013-05-30en_US
dc.date.issued1970-05en_US
dc.description.abstract<p>Kinchla (1969 ) has proposed a general model for multiple observation tasks which assumes that humam observers respond in such tasks on the basis of the sum of the sensory information available to them. In this thesis Kinchla's simple sum model is compared to a model which assumes that observers respond on the basis of the weighted sum of the sensory information available to them.</p> <p>Three experiments were carried out. The major findings were that in a two interval sequential multiple observation task:</p> <p>1) Stimulus Frequency within an interval does not induce weighting.</p> <p>2) Instructions to concentrate on one interval induce weighting.</p> <p>3) False information feedback about one interval induces weighting.</p> <p>The relevance of the results to theories of "attention" is discussed.</p>en_US
dc.description.degreeDoctor of Philosophy (PhD)en_US
dc.identifier.otheropendissertations/7819en_US
dc.identifier.other8912en_US
dc.identifier.other4186970en_US
dc.identifier.urihttp://hdl.handle.net/11375/12980
dc.subjectPsychologyen_US
dc.subjectPsychologyen_US
dc.titleStatistical Decision Theory Models of Sequential Multiple Observations by Human Observersen_US
dc.typethesisen_US

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