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Datenvisualisierung für Exploration und Inferenz

  • Richard TraunmüllerEmail author
Living reference work entry
Part of the Springer Reference Sozialwissenschaften book series (SRS)

Zusammenfassung

Datenvisualisierung ist eine der effektivsten Methoden, um quantitative Information zu explorieren, zu beschreiben und zu kommunizieren. Dieser Beitrag diskutiert, welche Ziele Datenvisualisierung verfolgt und was sie zu einem analytischen Werkzeug macht. Zum einen wird Visualisierung für den wichtigen Schritt der Datenexploration beschrieben. Exemplarisch wird dabei vor allem auf table plots, parallel coordinate plots und small multiple designs eingegangen, die sich für die Visualisierung mehrdimensionaler Datenstrukturen eignen. Zum anderen werden visuelle Methoden der Inferenz in den Blick genommen: visuelle statistische Inferenz, in welcher Grafiken den Platz von Teststatistiken einnehmen, die Visualisierung inferentieller Unsicherheit und statistischer Modelle, sowie schließlich die Exploration von Modellunsicherheit.

Schlüsselwörter

Datenvisualisierung Explorative Datenanalyse Statistische Grafiken Statistische Inferenz Visuelle Inferenz 

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Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019

Authors and Affiliations

  1. 1.Institut für PolitikwissenschaftGoethe-Universität FrankfurtFrankfurt am MainDeutschland

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