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Kontingenzanalyse 1Gliederung der Vorlesung
1) Grundlagen
2) Datendeskription
3) Zusammenhangsanalyse und Regression Das Buch Kapitel 8 und 9.
a) Diese Woche: Kontingenzanalyse: Kapitel 8.1.
b) Korrelationsanalyse, lineare Regression.
4) Wahrscheinlichkeiten, Zufallsgrößen
5) Induktive Statistik
HTW Berlin
,Kontingenzanalyse 2
Zusammenhangsanalyse
Wir betrachten hier 2 Merkmale (bivariate Analyse) und wollen
untersuchen, ob es einen Zusammenhang zwischen den beiden gibt.
Dabei kommen folgende Methoden in Betracht:
• Kontingenzanalyse: geeignet für zwei diskrete Merkmale mit relativ
wenigen Ausprägungen. Es können nominale, mit Einschränkungen
auch ordinale oder klassierte metrische Merkmale sein. Das werden
wir hier anwenden.
• Korrelationsanalyse: für metrische Merkmale mit vielen
Ausprägungen geeignet. Das machen wir nächste Woche.
• Z.B. Rangkorrelationsanalyse. Das machen wir nicht in diesem Kurs.
HTW Berlin
, Kontingenzanalyse 3
Zusammenhangsanalyse: Beispiel
Wir untersuchen, ob Interesse für Reisen und Interesse für Kultur (jeweils ja/nein
Angaben) bei Partnersuchenden eines Online-Partnerportals voneinander unabhängig
sind.
HTW Berlin
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