Ruprecht-Karls-Universität Heidelberg
Siegel der Universität Heidelberg

Module for [Scientific Computing]

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[Statistics II] - [2015 Sommer]

Module Code
MH12a
Name
Statistics II
Credit Points
8 CP
Workload
240 h
Duration
1 semester
Cycle
0
Methods Lecture 4 h + Exercise course 2 h
Objectives To have a firm understanding of the advanced statistical methods for iid and non-iid data
Content • Estimation and prediction methods for linear models • Order statistics; estimation of quantiles • Empirical processes; hypothesis testing • Asymptotic theory for U-Statistics • Non-parametric estimation methods; kernel density estimator
Learning outcomes • firm understanding of the advanced statistical methods for iid and non-iid data
Prerequisites
Suggested previous knowledge MC4 or equivalent; MD2 or equivalent
Assessments TBD (typically, homework and written exam)
Literature H. David and H. Nagaraja: Order Statistics. Wiley, 2003.
D. Pollard: Convergence of stochastic processes. Springer, 1984.
A.W. van der Vaart: Asymptotic Statistics. Cambridge University Press, 2000.
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