On the factors shaping numerical real-world estimation


Kreis, Barbara K.


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URN: urn:nbn:de:bsz:180-madoc-721031
Document Type: Doctoral dissertation
Year of publication: 2026
Place of publication: Mannheim
University: Universität Mannheim
Evaluator: Bröder, Arndt
Date of oral examination: 2025
Publication language: English
Institution: School of Social Sciences > Allgemeine Psychologie (Bröder 2010-)
Subject: 150 Psychology
Keywords (English): numerical estimation , symbolic-number mapping , seeding , hindsight bias
Abstract: Numerical estimation is a fundamental cognitive skill supporting numerous everyday decisions. Yet, our understanding remains fragmented. This dissertation addresses this gap by examining numerical real-world estimation through the factors that shape it. With Manuscript I, I broaden the understanding of the foundations of numerical estimation by showing that, beyond domain knowledge, symbolic-number mapping also underlies estimation. In Manuscripts II and III, I deliberate how estimation changes when the knowledge base is updated. In Manuscript II, I examine how providing information can trigger knowledge updating and thus improve estimation. In Manuscript III, I investigate hindsight bias—the tendency to recall prior estimates as more accurate after learning the actual values. I provide evidence that this bias arises from the same updating processes that improve estimation. With this dissertation, I deepen our theoretical understanding of the factors shaping numerical real-world estimation while providing guidance for supporting estimation accuracy.




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ORCID: Kreis, Barbara K. ORCID: 0000-0002-8520-6475

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