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Institute of Applied Statistics
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Bachelor's Thesis

Members of the IFAS with Phd. supervise Bachelor and Master theses in Statistics , preferably in the following areas and serve as examiners for the Master’s examination:

Duller

Nonparametric Statistics

Futschik

Modelling of High-Dimensional Data, Approximative Inference, Biostatistics and Modelling of Genomic Data

Hainy

Computational Statistics, Bayes Statistics, Supervised Learning

Müller

Experimental Design, Econometrics, Spatial Statistics

Quatember

Survey Statistics and related topics

Stehlík

Risk Management, Experimental Design, Pension Systems

Wagner

Time-Series Analysis, Analysis of Longitudinal Data, Survival Analysis, Bayes-Statistics, Medical Statistics

Waldl

(Generalized) Linear Models, Factor Analysis

Currently the following topics for Bachelor theses are offered for supervision amongst others:

Duller

• Nonparametric Permutation Tests
• Nonparametric Tests for Umbrella Alternatives
• Digital Learning: Basic Statistics
• Digital Learning: Nonparametric Statistics

Futschik

• Effects of Violation of Model Assumptions on Statistical Methods
• Theory of Probability in Pictures: Visualisation of Important Results of Probability Theory
Hainy:

• Shiny-App zur Simulation epidemiologischer Prozesse

• Comparison of methods for conditional density estimation

Müller

• The Variance of the Sample Median
• Estimation of COVid-19 prevalence by means of Approximate Bayesian Computation

• Machine Learning using OfficeCalc

• Counterexamples to the Lindeberg-Lévy theorem

• Analysis of wordle.at strategies

Quatember

• The problem of statistical surveys on sensitive topics

• The estimation of the size of a population

• Sample surveys of official statistics

Stehlík

• Modelling and prediction of the spread of the coronavirus disease 2019

• Financial risk management and pension systems

• Intelligent neural networks

• Time series modelling by neural networks

• Statistical modelling of ecological problems

• Statistics in medicine

Wagner:

• Estimation of heterogeneous treatment effects via propensity score matching
• Statistical analysis of  fmri data  in R
• Statistical inference for fmri data
• Bayesian methods in meta analysis
• Meta regression
• Analysis of compositional data

 

Waldl

• Confirmatory Factor Analysis and Structural Equation Modelling

• Bias-Variance-trade-off in general linear models

• Double Generalized Linear Models

• Operationales Risiko: Verlustverteilung mit Monte Carlo Simulation (in Kooperation mit der Oberbank)

Information regarding the Bachelor's Thesis can be found here. The template for the layout of the Bachelor's Thesis can be found below.