Accession Number : ADA104372


Title :   Prediction, Diagnosis, and Casual Thinking in Forecasting.


Descriptive Note : Interim technical rept.,


Corporate Author : CHICAGO UNIV IL CENTER FOR DECISION RESEARCH


Personal Author(s) : Einhorn,Hillel J ; Hogarth,Robin M


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a104372.pdf


Report Date : 03 Sep 1981


Pagination or Media Count : 40


Abstract : While forecasting involves forward/predictive thinking, it depends crucially on prior diagnosis for suggesting a model of the phenomenon, for defining 'relevant' variables, and for evaluating forecast accuracy via the model. The nature of diagnostic thinking is examined with respect to these activities. We first consider the difficulties of evaluating forecast accuracy without a causal model of what generates outcomes. We then discuss the development of models by considering how attention is directed to variables via analogy and metaphor as well as by what is unusual or abnormal. The causal relevance of variables is then assessed by reference to probabilistic signs called 'cues to casuality'. These are: temporal order, constant conjunction, contiguity in time and space, number of alternative explanations, similarity, predictive validity, and robustness. The probabilistic nature of the cues is emphasized by discussing the concept of spurious correlation and how causation does not necessarily imply correlation. Implications for improving forecasting are considered with respect to the above issues. (Author)


Descriptors :   *PERFORMANCE(HUMAN) , *MATHEMATICAL LOGIC , *FORECASTING , DATA BASES , INTEGRATED SYSTEMS , MESH , CORRELATION TECHNIQUES , PERCEPTION , SPURIOUS EFFECTS


Subject Categories : Psychology
      Statistics and Probability


Distribution Statement : APPROVED FOR PUBLIC RELEASE