Introduction to collaborative social science data analysis

The objective of this course is to learn how to collaboratively and reproducibly gather social data, analyse it, and effectively present results. It is intended to be immediately useful for your academic work, as well as work in the public and private sectors. The tools you learn and the final project you complete in this course will be directly useful for your thesis research. 

The course will involve learning the fundamentals of the collaborative and reproducible research process from data gathering, analysis and presentation with widely used computer languages and statistical techniques. The R statistical language will allow us to gather and analyse our data. The Markdown/HTML markup languages will allow us to present our results to a variety of audiences. We will use Git/GitHub to version control and store all of our files. This will enable research collaboration and full reproducibility. 

Students will learn how to use these tools through active in class participation and collaboration on realistic projects using the concepts and tools introduced in lectures and scholarly articles. The course assumes that you have a basic understanding of descriptive and introductory inferential statistics (e.g. data types, ways of describing distributions, significance testing, linear models). Knowledge of particular software or computer programming is not assumed.

This course is for 2nd year MIA and MPP students only.