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Explorative Werkzeuge

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Statistik in Theorie und Praxis

Part of the book series: Mathematik für das Lehramt ((MATHLEHR))

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Zusammenfassung

Am Beginn der Datenanalyse, vor dem Einsatz von Schätz- und Testverfahren, sollte man sich zuerst die zu untersuchenden Daten visualisieren, gemäß dem Zitat des bekannten Statistikers John W. Tukey in [5]:

  • There is no excuse for failing in plot and look.

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Literatur

  1. Dalal, S.R., Fowlkes, E.B. und Hoadley, B. (1989). Risk analysis of the space shuttle: Pre- Challenger prediction of failure. J. Amer. Statist. Assoc. 84, 945–957.

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  2. Falk. M, Becker, R. und Marohn, F. (2004). Angewandte Statistik. Springer, Berlin-Heidelberg.

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  3. Hain J. (2011). Statistik mit R – Grundlagen der Datenanalyse. RRZN-Handbuch, Leibniz Universität Hannover.

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  4. Hand, D.J, Daly, F., Lunn, A.D., McConway, K.J. und Ostrowski, E. (1994). A handbook of small data sets. Champman & Hall, London.

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  5. Tukey, J.W. (1977). Exploratory Data Analysis. Addison-Wesley, Reading.

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  6. Weiß, C.H. (2006). Datenanalyse und Modellierung mit STATISTICA. Oldenbourg, München.

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Author information

Authors and Affiliations

  1. Institut für Mathematik, Universität Würzburg, Würzburg, Deutschland

    Michael Falk, Johannes Hain & Frank Marohn

  2. Mathematisch-Geographische Fakultät, Katholische Universität Eichstätt-Ingolstadt, Eichstätt, Deutschland

    Hans Fischer

  3. Altran GmbH & Co. KG, Frankfurt am Main, Deutschland

    René Michel

Authors
  1. Michael Falk
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  2. Johannes Hain
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  3. Frank Marohn
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  4. Hans Fischer
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  5. René Michel
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Corresponding author

Correspondence to Michael Falk .

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Falk, M., Hain, J., Marohn, F., Fischer, H., Michel, R. (2014). Explorative Werkzeuge. In: Statistik in Theorie und Praxis. Mathematik für das Lehramt. Springer Spektrum, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55253-3_1

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