During this one week program you will work together with other entrepreneurs on improving your business or business concept. We will give you a proven methodology for assessing and shaping your venture.
This course provides a general survey of the methods used to analyze panel data (i.e., data with units observed repeatedly over time). It places a special emphasis on causal inference, which is a primary goal of social sciences.
The course will introduce statistical models for network data and other data with complex dependence among observations. A range of models will be discussed theoretically, in application and using R.
Join for a week-long journey into R programming for data analysis. From mastering R basics and data import to advanced skills in cleaning, visualization, and analysis, this course integrates theory with hands-on exercises.
This hands-on course aims to strengthen your ability to use process tracing methods in their own research. The course is designed for those who are actively engaging in process tracing research.
The course will explore the dynamic intersection of spatial analysis and social sciences using R. It will equip you with essential skills to analyze geographical data, map social phenomena, and uncover spatial patterns.
This course focuses on the use of digital technologies for qualitative data collection, from a conceptual to applied perspective, including logistical, technical and ethical issues.
The course covers the basics of programming in R. Besides that, it also covers working in RMarkdown, which allows you to generate an entire research paper with RStudio.
It introduces the key CHA tools, contrasts with conventional variance-based approach, and helps you to apply them to your problem-driven and hence most likely, historical projects
Radboud University
