R-Workshop (Promovierende, Postdocs, Habilitierende)
14 & 15 July 2021
Time: 9:00am - 5:00pm, 9:00am - 1:00am
Registration: until 30 June 2021
for doctoral candidates via BayDOC: https://baydoc.uni-bayreuth.de
for postdocs and habilitation candidates via WiN-UBT Portal
- Short Introduction into the User Interface.
- Import Data from Excel and Handle Data in R
- Descriptive Statistics: Mean, Median, Quantiles, Standard Deviation, Correlations (Pearson, Spearman), Scatterplots (and Graphical Parameters), Boxplots, Histograms, Bar Plots
- R Scripts, R Packages, R Help and Books
- Comparing Means (and Medians): Confidence Intervals, Popular Tests for
- Comparisons, (t-Test, Mann-Whitney/Wilcoxon, Kruskal-Wallis, . . . )
- Check of Assumptions: Testing Normality, qq-Plots, Homoscedasticity: Variance Homogeneity (Levene)
- Principal Components Analysis
- Linear Regression and Analysis of Variance: Introduction into Linear Regression with R, ANOVA, MANOVA, Post-Hoc-Tests, Generalized Linear Regression (logistic, probit)
- Repeated Measurements (Longitudinal Studies)
This is a hands-on workshop which includes exercises in which participants analyze data in R on the computer.
Being able to analyze data in R
- This is a basic course on R and it does not assume any preknowledge on R.
- The course assumes at least a basic knowledge on statistics: mean, standard deviation, median, quantile, confidence interval, hypothesis testing, p value, significance, linear regression.
- An optimal prerequisite would be knowledge of (nearly) all of the statistical methods covered in the workshop. Though all of these methods are quickly recapitulated in the workshop, learning R is easier if the statistical methods are already known.
- Diploma in Mathematics (2001-2006)
- Ph.D. Thesis at the Department of Statistics at LMU Munich (2006-2009)
- Akademischer Rat a. Zt. At the University of Bayreuth (2009-2014)
- Habilitation on machine learning at the University of Bayreuth (2012)
- Associate Editor for the journal Statistics & Probability Letters
- Author of numerous articles on statistics and machine learning, author of a textbook on stochastic theory
- 2014-2019: Head of „Big Data Analytics“ at Technologiecampus Grafenau at TH Deggendorf; statistical consultant
- Since 2019: Professor for Artificial Intelligence at TH Deggendorf