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In regression, the dependency of a random response variable on other variables is examined. We consider the theory of linear regression with one or more covariates, high-dimensional linear models, nonlinear models and generalized linear models, model choice and nonparametric models. Several numerical examples will illustrate the theory.
Learning objective
- Thorough, theoretical understanding of linear regression - Overview of several extensions of linear regression - Ability to correctly apply the methods learned in simple data examples
Content
In der Regression wird die Abhängigkeit einer beobachteten quantitativen Grösse von einer oder mehreren anderen (unter Berücksichtigung zufälliger Fehler) untersucht. Themen der Vorlesung sind: Einfache und multiple Regression, Theorie allgemeiner linearer Modelle, Hoch-dimensionale Modelle, Ausblick auf nichtlineare Modelle, Modellsuche, Residuenanalyse, nicht-parametrische Regression. Durchrechnung und Diskussion von Anwendungsbeispielen.
Prerequisites / Notice
This is the course unit with former course title "Regression". Credits cannot be recognised for both courses 401-3622-00L Statistical Modelling and 401-0649-00L Applied Statistical Regression in the Mathematics Bachelor and Master programmes (to be precise: one course in the Bachelor and the other course in the Master is also forbidden).
Competencies
Subject-specific Competencies
Concepts and Theories
assessed
Techniques and Technologies
assessed
Method-specific Competencies
Analytical Competencies
assessed
Decision-making
assessed
Problem-solving
assessed
Personal Competencies
Adaptability and Flexibility
fostered
Creative Thinking
fostered
Critical Thinking
assessed
Self-direction and Self-management
fostered
Performance assessment
Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course