Overconfidence and Format Dependence in Subjective Probability Intervals: Naive Estimation and Constrained Sampling

A particular field in research on judgment and decision making (JDM) is concerned with realism of confidence in one’s knowledge. An interesting finding is the so-called format dependence effect which implies that assessment of the same probability distribution generates different conclusions about over- or underconfidence bias depending on the assessment format. In particular,expressing a belief about some unknown quantity in the form of a confidence interval is severely prone to overconfidence as compared to expressing the belief as an assessment of a probability. This thesis gives a tentative account of this finding in terms of a Naïve Sampling Model (NSM;Juslin, Winman, & Hansson, 2004), which assumes that people accurately describe their available information stored in memory but they are naïve in the sense that they treat sample properties as proper estimators of population properties. The NSM predicts that it should be possible to reducethe overconfidence in interval production by changing the response format into interval evaluation and to manipulate the degree of format dependence between interval production and interval evaluation. These predictions are verified in empirical experiments which contain both general knowledge tasks (Study 1) and laboratory learning tasks (Study 2). A bold hypothesis,that working memory is a constraining factor for sample size in judgment which suggests that experience per se does not eliminate overconfidence, is investigated and verified. The NSM predicts that the absolute error of the placement of the interval is a constant fraction of interval size, a prediction that is verified (Study 2). This thesis suggests that no cognitive processing bias(Tversky & Kahneman, 1974) over and above naivety is needed to understand and explain the overconfidence bias in interval production and hence the format dependence effect