79296 - Advanced Analysis of Data

Course Unit Page

Academic Year 2021/2022

Learning outcomes

By the end of the course the student will develop advanced expertise in formulating and implementing statistical approaches to practical problems in a wide variety of subject areas. To integrate material covered in various lecture courses with skills developed through practical work in order to solve real-world problems. By the end of this course students will be able to: - formulate questions of interest and identify relevant informal and formal statistical methodology for a wide variety of practical contexts; - implement the various stages of advanced statistical analysis appropriately in R; - interpret the output of R procedures; - critically collate results and conclusions; - present the main results and conclusions in the form of concise summaries; - present results of analyses in the form of written reports; - critically assess published applications of statistical analysis; - work independently on practical data analysis problems.

Course contents

The course will confront the student with a number of case studies covering different areas such as missing values, regression and related methods, time series and modelling, analysis of ordinal and categorical data.


Readings/Bibliography

To be posted on Virtuale.

Teaching methods

In-class lectures, group work on data sets, student presentations and discussions

Assessment methods

The course will be assessed by the reports that the groups write and submit on the case studies during the course. Every student also has to present case study results once. Students who cannot give a presentation during the course will be examined orally on flexible individually agreed dates. Missing reports have to be submitted at later deadlines individually (without group work).

The course is not marked quantitatively, but as "idoneo/non idoneo".

Teaching tools

Supporting material to be posted on Virtuale.

Office hours

See the website of Christian Martin Hennig