ANU Online Winter School in Political Analysis (SSPA)

11-29 July 2022 

REGISTRATION DEADLINE: 30 June 2022

Advanced and foundational studies in political analysis and research methods. Hosted by the Australian National University’s School of Politics & International Relations (SPIR).

Research training for tomorrow's world

2022 sees the global community facing significant challenges — politically, economically, socially and environmentally. It’s a world that’s fraught with uncertainty, but it’s also a future that will rely on the expertise of academics and professionals in political science to help navigate the road ahead. In July 2022, the School of Politics and IR will host a fully online summer school in Political Analysis. We will provide a sequenced combination of foundational and advanced short-course topics focused on methods in political science. 

Who should take part?

The SSPA has been created to meet the needs of:

• University graduates pursuing or seeking to pursue PhD degrees in political science at ANU and other Australian universities
• International political science graduates pursuing or seeking to pursue advanced studies or enhance their skills and employability in political analysis
• Professional political science researchers in academia and policy organisations

Small cost, big benefit

Each course has been designed to deliver a fully interactive and informative learning experience that will make an invaluable contribution to your academic or professional development — and at a cost that should prove a sound investment for you or your institution to make. 

The SSPA comprises:

• Each course (5 half-day sessions 9.00am to 11.30am) costs $750AUD.

LINK TO BOOKING/PAYMENT (ANU Students will receive a 20% discount. Students from wthin the ANU Research School of Social Sciences please contact admin.rsss@anu.edu.au to arrange payment)

Teaching quant with R

R is a free and increasingly common statistical computing tool for political science researchers. Unless stated otherwise, quantitative courses in our summer school are taught using R. Keeping our course stack within R eliminates unnecessary cost in training and equipping students, while at the same time streamlining course progression.