After successful completion of the course, students are able to

• understand theoretical and practical concepts of important exploratory data analysis techniques
• understand the strengths and weaknesses of the different statistical methods and tools

sampling design, statistical sampling design, elements of exploratory data analysis,

basics of parametric, non-parametric and robust procedures, linear models,

introduction to multivariate statistical methods, introduction to time series analysis

efficient programing in the statistical software environment R, data manipulation, statistical graphics, graphical systems in R, dynamic reports with statistical software, application to real problem settings.

The Data Analysis course provides both theoretical access to the methods, but also demonstrates the practical solution using statistical software. The students should solve problems independently using the computer.

Please, register via TISS!

There are computer exercises, and the material is available in TUWEL.
Your registration data are taken directly from TISS.

Solving examples in R, oral exam

Basic knowledge in mathematics and statistics

Such prerequisites can be obtained in the following modules: STW/ADM – Algebra
und Diskrete Mathematik, STW/ANA – Analysis, STW/STA – Statistik und Wahr-
scheinlichkeitstheorie