Data Analysis and Statistical Interface with R

We live in a world full of data and ever more decisions are taken based on a comprehensive analysis of data. This course provides an introduction to quantitative data analysis using graphical representations, numerical summary statistics, correlation and simple regression. It also introduces the fundamental concepts of statistical inference. Students learn about the different data types, how to best visualize them and how to draw conclusions from the graphical representations. The lecture will develop the different steps and ingredients of hypothesis testing by focusing on the practical aspects. Students will learn how to become an intelligent user of basic statistical techniques from a prosumers perspective in order to assess the quality of presented statistical results and to produce high quality analysis by themselves. By using illustrative examples from economics, engineering, the natural and social sciences students will gain the relevant background knowledge for their specific major as well as an interdisciplinary glimpse to other research fields. Regular exercises, homework assignments and practical sessions using the statistical software R will enhance the students’ learning experience.