Please, make a reboot of this course with some improvements in the material.

More examples

More solved exercises.

More homework.

Thankful that a course like this exists, as most MOOCs are quite basic. And thanks to Coursera for running the courses even though attendance seems to be low (darn, that pesky calculus pre-requisite). Lecture quality is varied--some quite good (such as the lectures in Boot Camp I) and others seem like he hadn't looked at his notes for a long time. It's great to hear a stats professor talk about the strengths and weaknesses of many approaches. It complements a mathematical statistics book quite well. It would have been nice to have had some problems that were more challenging. Overall, while the Johns Hopkins Data Science MOOCs are pretty good, they are a bit more basic than what's available through MIT and Stanford.

The course is a bit chaotic.

Again, high quality videos as the first course. And same problems as the first course, which are lack of support in the discussion forums and no answers for the quizzes.

The last week was a bit rushed and unclear.

This course should be part of the Data Science specialization. Actually, you can supplement the Statistical Inference course with these two Boot camp courses really well!

A great revision of statistics, very rigorous and thorough cover of all distributions and hypothesis tests.

The course is extremely structured. It is a fantastic "boot camp" for students who would like to learn statistics, opening the door of future data analysis.

Fantastic introduction for statistics. Some quiz questions do not contain all the information required to answer them.

Outstanding professor -- more rigorous than other similar classes. Just the right degree of challenge in the quizzes.

Thank you Dr Brian for the in-depth teaching from fundamental to application in real-world healthcare research

Excellent! A great leading course to build up one with clear background to explore the data science.

Great course, although some topics require additional knowledge

This is amazing course for reviewing categorical statistics.

it is very useful to improve my knowledge

EXCELLENT - CONTENT AND DELIVERY.

It's very much informative

Great...

5

Goode videos and teacher. The videos are old and it will be perfect to refresh them and make it more interactive.

Quite a different course as compared to Mathematical Biostatistics Boot Camp 1. Many different tests for contigency tables are presented, however, without the proper mathematical derivation. It is just: Here is another test for this - more like a cookbook. Videos and quizzes are sometimes incoherent as if being put together from different sources without much care.

It was very challenging. It would be better if a couple of practice exercises were put after the relevant lecture videos and not just after the weekly lecture videos.

The instructor does a poor job of conveying information and seems to spend most of his time demonstrating that he understands the subject well. He would do better to focus on core concepts instead of talking through tangent details and implications of them. He expects the learner to visualize everything he is saying, which is mostly impossible without any prior understanding of the subject (which ... the learner does not have or they would not be taking this course.)

Inadequate homework assignments to support learning, so you'll have to spend a lot of time beyond the course's weekly time estimate. You might as well just watch lectures on YouTube and read Wikipedia, that's what I end up doing anyway.

"much better than the data science with R concentration provided also by John Hopkins. This course has concrete examples, and the lecturer doesn't treat his audience like the first-grade kids." I take this back. The lecturer doesn't know what he's taking about and what he is gonna talk about for at least half of the time.

From the practicioner's point mostly, not really mathematical