his is a two day course which will be taught over four mornings.
The fact that correlation does not equate to causation is so well known that it has become a popular saying in itself. Yet the way that quantitative analysis is discussed in much popular and political discourse, as well as interpreted by many social scientists, fails to take issues surrounding causality fully into account. This may be because randomized control experiments, widely understood as the most defensible method of establishing causality, are frequently impossible or unethical to conduct in social science settings.
Analysts thus have to work with observational data, which often miss information crucial for making causal interpretations of statistical associations. However, under some circumstances and subject to specific assumptions, one can interpret estimated associations as casual with substantially higher confidence. This course deals with methods that can be used under such circumstances and subject to the specific assumptions. The course offers practical skills in implementing these methods and the theoretical skills needed to understand and discuss evidence from them.
Presented by:
Dr Renee Luthra
Date & time:
March 23, 2021 9:00 am - March 26, 2021 1:00 pm
Venue:
ONLINE