Lecturer
Prof. Dr. Volker Schmidt

Teaching assistant
Dipl.-Math. David Neuhäuser

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Time and place

Lectures
Monday, 10-12 in H14

Exercise session
Wednesday, 12-14 in H14 (every 2 weeks only)

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Type

2 hours lecture + 1 hour exercises (Credit points: 4)

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Prerequisites

Probability Calculus, Stochastics I

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Intended Audience

Bachelor/Master students in Mathematik, Wirtschaftsmathematik, Mathematische Biometrie and Finance, Diploma students in Mathematik, Wirtschaftsmathematik.

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Contents

Main topics of the lecture are:

• multivariate normal distribution
• linear und general linear models
• Non-parametric tests

A current version of the manuscript can be found here.

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Exercises

Sheet 1

Sheet 2

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Requirements and Exam

In order to become accredited for the written exam, one has to earn 50% of all homework credits.

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Literature

 

• Büning, H., Trenkler, G. (1994)
  Nichtparametrische statistische Methoden
  de Gruyter, Berlin

• Cressie, N.A. (1993)
  Statistics for Spatial Data
  J. Wiley & Sons, New York

• Dobson, A.J. (2002)
  An Introduction to Generalized Linear Models
  Chapmen & Hall, Boca Raton

• Hastie, T., Tibshirani, R., Friedman, J. (2001)
  The Elements of Statistical Learning
  Springer, New York

• Koch, K.R. (1997)
  Parameterschätzung und Hypothesentests in linearen Modellen
  Dümmlers-Verlag, Bonn

• Lehmann, E.L. (1999)
  Elements of Large-Sample Theory
  Springer, New York

• Lehmann, E.L., Romano, E.J. (2005)
  Testing Statistical Hypotheses
  Springer-Verlag, New York

• Vapnik, V.N. (1998)
  Statistical Learning Theory
  J. Wiley & Sons, New York