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Making Sense of Data: Handling, Processing, Visualising, Spatial Mapping, Estimating, and Analysing Data in R

This course is fully booked and closed for further applications

The students will develop skills to conduct their own data management and analysis. They will be introduced to relevant concepts, terminology, and methods for handling data and spatial information in R and QGIS. At the end of the course, students will have a toolbox of scripts enabling them to optimise data management procedures by looping through data and using vector-oriented iterative processes. They will work in R studio, writing and debugging code for merging datasets, data cleaning and coding of different types of variables, as well as overlaying spatial data. They will be introduced to basic procedures for testing hypotheses. This includes tabulating basic statistical measures, specifying regression models, and interpreting and visualising results. Throughout the course, the focus will be on making data handling process transparent and reflecting on the implications of data management and statistical approaches in relation to the validity and reliability of the results of the analysis and good scientific practice.

Exam info and full course description

Exam info and full course description can be found in the course catalogue.

Admission Requirements

Course specific:

A bachelor's degree in Political Science.

Experience with data handling is a benefit; however, it is not a prerequisite.

General:

Exchange students: nomination from your home university

Freemovers: documentation for English Language proficiency

You can read more about admission here.

Lecturer