This class is okay. I think there are some good things about it. I'll start with those. First, the instructor does not dumb the math down, which I respect. It does feel like some of the other MOOCs soften the math to make customers happier, and this course does not do that. My brain hurt at a few points, but I'm assuming this is good pain. You will definitely feel more confident in your math abilities after completing this course. I also really appreciated having someone explain why we use things like the t-distribution or the chi-2 distribution, rather than just presenting them as magic. So that stuff is great.

My complaints are mostly connected with the non-credit version of the course. Basically, this course charges a lot, even if you are not taking it for credit. The average I've seen is $39 a month, and this charges twice that at $79. I would say that is not a big deal, except that Boulder also provides less support than your average Coursera course. And by less support I mean none. Most other courses I've taken do seem to have some moderator who will answer questions in the discussion forum. I have not seen any moderator for this course. I have not had any of my questions answered. Boulder is not interested.

This wasn't really a problem for the first course in the series, "Probability Theory," because that course provided a lot of different kinds of assignments to help you master and understand the concepts. So I felt like the course was still worth the extra price. But the assignments here are almost entirely quizzes, and a lot of the material is much harder to understand. Despite passing all the quizzes in weeks 2 and 3 on the first try, I don't really feel like I have a good handle on what was going on in those modules. And the course does not recommend any additional resources--problem sets you can work on on your own, reading, etc--to help get a better understanding of what's going on. A lot of the difficult mathematics in the quizzes felt more like proving you could do mental acrobatics than anything that would help you get the concepts.

I also think the instructor for this course and the instructor for the previous course in the series need to coordinate more. The first module of this course seems like it is supposed to be review of the topics covered in the previous one. But actually we are asked to do things that are much more complicated than the previous course covered, and we go through the material much more quickly. Either the previous course should be a bit harder, or this one needs to be toned down a bit.

So there are definitely things to like about this course. But I think Boulder needs to do more to justify the price tag.

The level of the Homework Questions and Programming assignments were far to difficult compared to what was taught in class. Additionally, I felt that the majority of the time, the logic of "just don't worry about this for now" was used, only to be required on a later question.

If you want to spend most of the time proving equations and doing math, this course is for you. If you're looking for useful stats for Data Science (as the course title implies) then I would suggest looking somewhere else. The course material also has plenty of typos and other errors that should have been corrected by now.

Quite a few technical issues with labs and programming assignments which prevent you from progressing in the course.

I feel like complaining it was very hard, but I can´t, it´s necessary. Jem Corcoran thruly wants you learn and share her experience with you. I recommend to go through the chapters again when finished, the concepts are not easy to digest at first.

Excellent presentation of the material! I wouldn't say it is an easy course though. I recommend really taking time to understand absolutely everything about each of the quiz problems. Doing the quizzes a second time really helped solidify the material for me.

The overall experience of the course was good but some of the questions were wacky at times

The course serves as a good reference for topics of interest, but I found the lectures very confusing, especially regarding MoM/MLEs. I felt confident coming out of the previous course in this series, but don't feel it prepared me for this course. The discussion forum is completely unresponsive. I struggled my way through the quizzes, but I don't feel I have a good grasp of the material. I had a frequent feeling of "where did that number/equation come from?" or "why do we do this that way, or set this equal to that?" etc etc. I may try to review this course material after reviewing some foundational topics.

There are SO many errors within the videos, the slides, the homeworks. The lectures don't give enough information to actually apply to any other problems - so you can't do the homework without extensive 'googling' to even get a hint of where to start on any of it.

The course has unsolvable tasks and you can never complete the course. The teacher is excellent, she knows how to explain very well, but the course assignments do not allow you to complete it

Excellent. Challenging quizzes that really make you apply the points from the lectures. Very detailed course that has taken me to the next level of my understanding of statistical inference.

The instrustor, Dr. Jem, is really interesting. She made the hard part of the Statistics easy to understand!

This course provided me with truly deep insights into the inner workings of statistics. Thank you very much.

Jem Corcoran es una gran docente. Me encanto el curso!

It was a tough one for me... completely worth it.

Excelente conteúdo e práticas

In depth understanding

This course was tough and I needed to research (i.e. google) additional material for many of the concepts covered in the lectures to fully grasp them. The professor goes through interesting examples in the videos but sometimes they are not closely related to the questions that show up in the quiz afterwards. The workload isn't too much but given the difficulty of the topics especially in weeks 2 & 3, some more example solves and supplemental material would have been helpful. Upon finishing the course I realize I've learned a lot so I think the topics covered are very good.

The course content is good and presentet in a very sympatic manner. But there are quite a few mistakes in the slides and in the videos, which makes it harder to follow

too hard

Lab Grader issues