Introduction To Causal Inference And Directed Acyclic Graphs
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- เผยแพร่เมื่อ 4 มิ.ย. 2024
- This is a recording of the UKRN online workshop "Introduction To Causal Inference And Directed Acyclic Graphs" held on Thursday 3 February 2022.
Facilitated by speaker Peter WG Tennant.
Learning objectives:
- Appreciate ‘description’, ‘prediction’ and ‘causal inference’ as three distinct scientific tasks requiring distinct scientific methods
- Understand the main features of causal directed acyclic graphs and how they can be used to plan and interpret causal analyses
- Appreciate some of the challenges and implications of using directed acyclic graphs in applied research
0:00:00 Part 1: Introduction to causal inference and directed acyclic graphs
0:45:19 Q&A
0:57:41 Part 2: Directed acyclic graphs in practice
1:39:17 Q&A
For more information on UKRN: www.ukrn.org or follow us on Twitter (@ukrepro)
Situates causal inferences in a broader, almost context that is enormously help understanding what causal graphs are trying to accomplish and how the complement existing approaches. Contextualizing methodology in such a way should be done far more often. Super helpful. Thanks.
This presentation feels so cathartic! Genius stuff, thank you!
Super helpful for my dissertation! Thanks!
Thanks Peter for the wonderful presentation!
Very clear presentation, thanks for sharing!
this is the best causal explanation ever, thank you
This is just brilliant! Thank you.
Great presentation Peter! Thank you 👏👏👏
Excellent presentation !
Helpful. Many thanks!!
Brilliant presentation!
Brilliantly presented 👏🏻
great lecture, well delivered and engaging
Brilliant!
Great lecture tx
Great talk! Are the slides available anywhere? Thnx
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