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Multiple lineare Regression - Theorie und Beispiel

Multiple lineare Regression - Theorie und Beispiel


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About the Book

Studienarbeit aus dem Jahr 2015 im Fachbereich Statistik, Note: 1,3, Brandenburgische Technische Universität Cottbus, Sprache: Deutsch, Abstract: In dieser Arbeit geht es un dieTheorie bzw. Herleitung der multiplen linearen Regression und ihre Anwendung an einem Beispiel mithilfe von R (Code im Anhang). Wenn danach gefragt wird, ob eine ausgewogene Ernährung das Herzinfarktrisiko reduziert, Führungskräfte überdurchschnittlich gut aussehen oder Kinder aus zerrütteten Familienverhältnissen häufiger zur Flasche greifen als andere, dann kann im Rahmen der Beantwortung dieser Frage eine Regressionsanalyse nützlich sein. Die Regressionsanalyse modelliert Zusammenhänge zwischen einer abhängigen Variable (aV) und einer (einfache Regressionsanalyse) oder mehreren (multiple Regressionsanalyse) unabhängigen Variablen (uV). Ein solches Modell wird auch häufig dafür verwendet, Vorhersagen über die Werte einer abhängigen Variable auf Grundlage der Werte der unabhängigen Variablen zu treffen oder um die Intensität der Beziehung zwischen den Variablen zu identifizieren. Wie auch bei der Korrelationsrechnung bedeutet ein Zusammenhang zwischen abhängigen und unabhängigen Variablen bei der Regressionsanalyse nicht gleichzeitig eine Kausalität. Im Rahmen der Regression wird zwar gegebenenfalls vor Beginn der Rechnung eine Kausalitätsvermutung aufgestellt; ob die unabhängige Variable allerdings als Ursache tatsächlich vor der Wirkung (auf die abhängige Variable) steht, kann lediglich schlüssig argumentiert werden. Stellt sich die Regressionsgleichung als geeigneter Schätzer für die abhängige Variable heraus, so bedeutet das nur, dass mithilfe der unabhängigen Variablen die abhängige Variable hinreichend gut geschätzt werden kann. Eine Form der multiplen Regression ist die multiple lineare Regression, auf deren Theorie im Folgenden kurz eingegangen und die anschließend an einem Beispiel demonstriert wird.


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Product Details
  • ISBN-13: 9783656903581
  • Publisher: Grin Verlag Gmbh
  • Binding: Paperback
  • Language: German
  • Returnable: N
  • Spine Width: 2 mm
  • Width: 148 mm
  • ISBN-10: 3656903581
  • Publisher Date: 19 Mar 2015
  • Height: 210 mm
  • No of Pages: 24
  • Series Title: German
  • Weight: 95 gr


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