Prior and Anchoring Biases on Magnitude Estimation from a Proper Noun

Isao OZAWA  Takashi TAKEKAWA  

Publication
D - Abstracts of IEICE TRANSACTIONS on Information and Systems (Japanese Edition)   Vol.J101-D   No.2   pp.405-413
Publication Date: 2018/02/01
Online ISSN: 1881-0225
Type of Manuscript: Special Section PAPER (Special Section on Human Communication)
Category: 
Keyword: 
bayesian approach,  mathematical model,  cognitive bias,  Log-Normal distribution,  Log-Student's t distribution,  

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Summary: 
Our numeric decisions are affected by a value presented in advance. Such cognitive tendency and the presented value are called anchoring bias and anchor, respectively. In this paper, we tried evaluating the anchoring bias quantitatively by magnitude estimation from name of Opabinia, an early Cambrian aquatic life. In the experiments, the subjects performed the magnitude estimation without anchor or after presentation of anchor. We focused on the probability distributions of magnitude estimation and developed a mathematical model which can reproduce the experimental results. In our model, the prior for the target magnitude and presented anchors obey Log-Normal or Log-Student's t distribution.