學生對 宾夕法尼亚大学 提供的 A Crash Course in Causality: Inferring Causal Effects from Observational Data 的評價和反饋

Good introductory course. I wish there were more quizzes (at least another 2 more), testing our knowledge of various formulae for computing IPTW (inverse probability of treatment weights), ITT (intent to treat) and at least one more lab in R

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.

It is a very useful course that combines conceptual and technical aspects of Applied Causal Inference.

The presentations are very clear, the Examples and Exercises (R-coded) have been very useful for me to practice specific R-packages.

Great course, especially if you are reasonably familiar with R and basic stats and interested in approaching causal analysis. Word of caution: If you have never used R, you will have trouble getting through some of the assignment.s

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!

Really wonderful course--I learned so much in the way of theory and practical application in R. Some links need to be updated and it would be best to provide students with answers to worked examples for the quiz questions.

A great start for those starting to explore causal inference. The somewhat dry delivery of the lectures is fully compensated by how clear and informative they are.

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

Well structured to provide solid understanding of fundamentals, good intuition, and a basic view of applying the covered material.

Great introduction. Immediately used new knowledge in current job (marketing data scientist). Recommended course to co-workers.

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

Excellent course. This course helped me to develop my intuition on some of the more abstract concepts in causality.

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

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

Excellent course, extremely well presented that helps clarify a lot of statistical concepts in an intuitive way.

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

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

Very enlightening. Well explained, and strikes a great balance between theory & practical aspects.

This course is actually great. It is a basic course but it does not mean it is for an amateur.

The best course on causal inference on Coursera. Lots of examples, easy to follow materials.

A clear and straight-to-the-point introduction to causality. I'm really enjoying the course!

Good course on the over view of Causality. Not too technical, but not too light and fluffy.

Extremely helpful for people who just started to do research on observational studies!

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

Great course. It is good for broad set of people with different level of math skill.