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Uncertainty estimation and the uncertaintyprobability shift under information load
Author(s) -
Driscoll James M.,
Corpolongo Michael J.
Publication year - 1980
Publication title -
behavioral science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 45
eISSN - 1099-1743
pISSN - 0005-7940
DOI - 10.1002/bs.3830250305
Subject(s) - discontinuity (linguistics) , estimation , function (biology) , computer science , metric (unit) , measurement uncertainty , mathematics , statistics , engineering , biology , mathematical analysis , operations management , systems engineering , evolutionary biology
The human organism functions as a decider in a variety of systems, particularly at the level of groups and organizations. Because of the importance of the human's decisions to the performance of these systems, it is desirable to understand how human decision makers respond to the uncertainty and handle the information within them. Three experiments are reported which deal with the human's response to uncertainty in decisions varying in objective uncertainty as measured by the information theoretic metric, H. Results confirm earlier findings that mean uncertainty estimates increase linearly with H from 0.2 to 2.8 bits where a discontinuity in the function occurs. The location of this discontinuity is shown to change with information processing load and to be as high as 3.8 bits under low load conditions. Uncertainty estimation proves to be rather robust under conditions of reduced supports for estimation, such as the elimination of anchors (sample stimuli). Finally, a shift also from uncertainty to probability estimation occurs at the discontinuity in the function and this shift is shown to be dependent on information processing load.