This course is intended for applied data analysts, including academics and postgraduate students, policy specialists and others. It will examine questions dealt with in public policy, the social sciences and industry, using real data. This includes surveys, and economics and public health data.

This is a problem-based course for subject matter experts who want to use R to take their quantitative analysis to the next level. By the end of the week you will be able to better conduct descriptive analysis and regression in R, and will be able to create impressive looking data visualisations.

R is open source and free. It is flexible, powerful and intuitive and it is excellent for data visualisation. As it is open source, R has thousands of developers in leading universities, corporate research labs and other institutions across the world. This means its capabilities tend to exceed competing software, with new packages added or updated daily. This is particularly the case for data visualisation, in which R tends to lead the pack. As there is no licence, you can take it with you wherever you go. No matter where you work, you don't have to change software packages when you change employers. Consequently, R has becoming increasingly popular for academic research, economics analysis and public policy development. This trend is only likely to continue.

Being skilled in R will help build your personal capabilities and employment opportunities by making you a more flexible worker capable of undertaking analysis many other researchers and analysts cannot.

No prior experience with R, or any sophisticated quantitative methods are required for this course. Participants should be computer literate and use data in their occupations (or study, if they are a student) and understand some of the basics of statistics. Some basic knowledge with regression is helpful, as is the ability to do simple coding and programming.

The unit will help build participants’ ability to work with data in R and undertake rigorous statistical analysis, including spatial analysis and linear regression, and create publication-standard graphs of the results. The end result will be more professional and easy to understand research.

You will need your own computer preloaded with R and an internet connection.
Access to Zoom.
We will be in contact prior to the course to ensure you have the software you'll need.
Data and course notes will be provided.