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Handbuch Methoden der Politikwissenschaft pp 1–32Cite as

Datenvisualisierung für Exploration und Inferenz

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Part of the book series: Springer Reference Sozialwissenschaften ((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.

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Notes

  1. 1.

    Das Eingangsbeispiel ist eine alternative Version von Anscombe’s (1973) klassischem Quartett, welches Forschern seit Jahrzehnten als Warnung dafür dient, Daten ‚unbesehen‘ zu modellieren.

  2. 2.

    Allerdings stellen zwei zentrale visuelle Methoden der univariaten Datenexploration – das Histogramm und der Box Plot – bereits Datenabstraktionen dar. Im ersten Fall durch die Klasseneinteilung und im zweiten Fall durch die erfolgende Zusammenfassung einer Verteilung anhand von fünf Werten plus eventuellen Ausreißern. Dadurch wird Informationsgehalt reduziert, und es ist durchaus möglich, wichtige Aspekte der Daten zu übersehen.

  3. 3.

    Die Daten stammen aus dem DFG-Projekt „Parlamentskandidaten in den Deutschen Bundesländern: Sozio-demographischer Hintergrund, Rekrutierung, Einstellungen, und Wahlkampf“. Ich danke Thomas Zittel für die freundliche Bereitstellung der Daten.

  4. 4.

    Ich danke Hårvard Hegre und Espen Rød für die freundliche Bereitstellung des Datensatzes.

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Author information

Authors and Affiliations

  1. Institut für Politikwissenschaft, Goethe-Universität Frankfurt, Frankfurt am Main, Deutschland

    Richard Traunmüller

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  1. Richard Traunmüller
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Correspondence to Richard Traunmüller .

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Editors and Affiliations

  1. Methodenzentrum Sozialwissenschaft, Goethe-Universität Frankfurt Methodenzentrum Sozialwissenschaft, Frankfurt, Hessen, Germany

    Claudius Wagemann

  2. Institute for Political Sciences, University of Duisburg-Essen Institute for Political Sciences, Duisburg, Germany

    Achim Goerres

  3. Institut für Politikwissenschaft, Goethe-Universität Frankfurt am Main Institut für Politikwissenschaft, Frankfurt, Hessen, Germany

    Markus Siewert

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Traunmüller, R. (2019). Datenvisualisierung für Exploration und Inferenz. In: Wagemann, C., Goerres, A., Siewert, M. (eds) Handbuch Methoden der Politikwissenschaft. Springer Reference Sozialwissenschaften. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-16937-4_5-1

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  • DOI: https://doi.org/10.1007/978-3-658-16937-4_5-1

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