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Covariation assessment in rank order data
Author(s) -
Bettman James R.,
Creyer Elizabeth H.,
John Deborah Roedder,
Scott Carol A.
Publication year - 1988
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.3960010404
Subject(s) - heuristics , rank (graph theory) , heuristic , set (abstract data type) , simple (philosophy) , statistics , data set , rank correlation , correlation , task (project management) , order (exchange) , psychology , computer science , mathematics , econometrics , artificial intelligence , combinatorics , mathematical optimization , philosophy , geometry , management , epistemology , economics , programming language , finance
Two experiments were conducted to investigate how individuals assess covariation with rank order data. In both studies, subjects were given sets of rank order data, each set consisting of ten items ranked on two characteristics, and were asked to estimate the degree of relationship for each set. Contrary to previous research, subjects' estimates of covariation in this task were quite sensitive to actual levels of correlation in the data and remained unaffected by simple variations in the way rank order data were presented. More importantly, it appeared that this sensitivity to covariation was due likely to the use of a simple heuristic referred to here as the total discrepancy heuristic. These findings are discussed in terms of the availability of simple heuristics in rank‐ordered versus other types of data and the consequences of using such heuristics in decision‐making contexts.