A Crash Course in Causality Inferring Causal Effects from Observational Data
We have all heard the phrase “correlation does not equal causation.” What, then, does equal causation? This course aims to answer that question and more! Over a period of 5 weeks, you will learn how causal effects are defined, what assumptions about your data and models are necessary, and how to implement and interpret some popular statistical methods. Learners will have the opportunity to apply these methods to example data in R (free statistical software environment).
At the end of the course, learners should be able to:
- Define causal effects using potential outcomes
- Describe the difference between association and causation
- Express assumptions with causal graphs
- Implement several types of causal inference methods (e.g. matching, instrumental variables, inverse probability of treatment weighting)
- Identify which causal assumptions are necessary for each type of statistical method
So join us…. and discover for yourself why modern statistical methods for estimating causal effects are indispensable in so many fields of study!
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Syllabus
Syllabus - What you will learn from this course
Week 1
Welcome and Introduction to Causal Effects
Week 2
Confounding and Directed Acyclic Graphs (DAGs)
Week 3
Matching and Propensity Scores
Week 4
Inverse Probability of Treatment Weighting (IPTW)
Week 5
Instrumental Variables Methods
FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Reviews
I enjoyed the course a lot and I think I took a lot from it as well. The quizzes and computer projects were appropriate, and the resourcees posted were very useful.
I completed all 4 available courses in causal inference on Coursera. This one has the best teaching quality. The material is very clear and self-contained!
It will be better to give reviews of related applications in specific AI areas (e.g, computer vision, NLP, etc.) at the end of each of the sections of the lesson.
Excellent course. Could use a small restructuring, as I had to go through the material more than once, but otherwise, very good material and presentation.
