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Confirmation: What's in the evidence?

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  • Mitesh Kataria

    (Max Planck Institute of Economics, Jena)

Abstract

In this paper, I discuss the difference between accommodated evidence (i.e. when evidence is known first and a hypothesis is the proposed to explain and fit the observations) and predicted evidence (i.e., when evidence verifies the prediction of a hypothesis formulated before observing the evidence) from a behavioral as well as a statistical perspective. Using a factorial survey on a sample of students, I show that predicted evidence is perceived to constitute stronger confirmation than accommodated evidence. This position deviates from the standard Bayesian epistemological theory of confirmation where accommodated and predicted evidence constitute equally strong confirmation. The findings suggests that trusting a model to predict correctly is intrinsically related to trust in the proposers' (i.e., the scientists') level of knowledge, and relatively more subjects are persuaded by a proposer's abilities if the proposer is successful in predicting rather than accommodating evidence. The existence of an indirect relationship between hypothesis and evidence can be considered to impose undesirable subjectivity and arbitrariness on questions of evidential support.

Suggested Citation

  • Mitesh Kataria, 2013. "Confirmation: What's in the evidence?," Jena Economics Research Papers 2013-025, Friedrich-Schiller-University Jena.
    • Handle: RePEc:jrp:jrpwrp:2013-025
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Evidence; Prediction; Methodology;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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