good

The course was good, but I found the answers to the assignments to be sometimes incorrect. In the failure responses, you can sometimes see that different input values than the ones given have been used..

Assignments are a mess, and apparently haven't been fixed for years after multiple complaints. Otherwise a good course, although not better than the one from U of PA, which was more accessible IMO.

Great course. Really interesting and condensed content. However, It was difficult to follow lectures without any kind of reading and there wasn't any support on the discussion forums.

The teacher is great, but some things could be explained more clearly. Also, there are some errors in the assignments. Other from that, totally worth it!

Lectures are informative, test questions practical. Whereas more delibration could be used to the writing of assessment questions and answers as there are obvious errors. Also, forum is not well-maintained leaving many questions unanswered for years.

Nice overview of topic but many quiz answers were wrong and haven't been corrected in over 5 years.

This course needs updating/a rework. The topics covered are great, but the assessment problems are out of date, sometimes wrong, or do not accept the correct answer. The ideas behind the syllabus here are exactly what I want from a mid-level/graduate intro to causal inference, but this is one of the worst courses I've ever taken on Coursera.

A talking lecturing on mathematics and statistics without any equations or slides. It's impossible to follow and the worst form of pedagogy. Coursera and Columbia should remove this course. It's embarassing.

Instructor does not use Notes, Whiteboard, etc. to demonstrate points. Written elaboration precedes verbal explanation in a statistics course!

Really bad