学生对 宾夕法尼亚大学 提供的 A Crash Course in Causality: Inferring Causal Effects from Observational Data 的评价和反馈

I enjoyed the course and learned basics of causal inference. What I missed was more exercises with R in order to gain more practical understanding of the material. In particular, it would be great to have exercises where you get some dataset and your task is to calculate given causal effect and you need to come up with an approach and to execute it. This would mimic more closely problems that you encounter in practice.

This course is quite useful for me to get quick understanding of the causality and causal inference in epidemiologic studies. Thanks to Prof. Roy.

The content is relaxing and easy to understand, yet extremely useful in real life when you are conducting experiments. The well designed quiz each week only takes a little time, but could help you to diagnose problems and remember the key points. I really love this course.

I learned the basics of causality inference and want even more now!

Excellent courses. I gain my expectations.

I was a novice in causal analysis. But I needed some education in counterfactual estimation. This course provided me with the necessary knowledge and tools. I especially enjoyed the matching, IPTW and IV chapters. Thank you!

Not only good for bio stats, it has also profound impact to my understanding of a/b testing in the internet world.

The best lecture series of causality

Excellent course! Can make it longer though and cover more details and latest advances and issues :-)

The material is great. Just wished the professor was more active in the discussion forum. Have not showed up in the forum for weeks. At least there should be a TA or something.

Excellent overview on causality inference and handling confounders combined with practical examples and R code.

enjoyed it very much

Great course for getting your hands dirty with some real causal methods.

Excellent course! The lectures are very clear and easy to follow, and Professor Roy is really good at explaining the concepts in a simple way. The assignments in R are helpful for grasping the theoretical concepts. I would specially recommend this course to data scientist, who might be interested in complementing their predictive analytics skills with the the necessary ones to tackle questions about causality.

Good intro of the techniques.

This is a great course for anyone interested in learning more about Causality and models for its estimation. I am a physician with limited statistical knowledge, but was able to follow this course with little difficulty, including analysis in R (though I do know how to run STATA and command line). I would recommend this course to anyone interested in performing a propensity matching study.

To those with some advanced statistics background, this would truly be helpful to catch up econometric thought processes.

Amazing Course! Really Helpful. I would love to have a similar full-duration course :D

Thanks so much for providing this great lecture.

Works best on double speed (from settings menu of each video). Content is delivered in clear and relatable manner using interesting real world examples.

One of the best courses in Coursera, Professor with lots of experience in a backpack show how to tackle very complex problem of causal inference. This is a topic every data analyst should know doesn't matter which industry you work or learn.

I really enjoyed this course, the pace could be more even in parts. Sometimes the pace could be more even and some more books/reference material for further study would be nice.

This course is really fantastic for all levels. Very thorough explanations and helpful illustrations. Many thanks for putting this together!

This is an excellent course taught by a very competent professor in a very simple to understand and intuitive way.

gives thorough basic intro to causal inference