Oct 26, 2018
Course is compressed with lots of statistical concepts. Which is very good as most must know concepts are imparted. Lots of extra reading is required to gain all insights. Very good motivating start .
Sep 25, 2020
the teachers were awesome in this course. I liked this course a lot.Understood it properly.Thanks to all the beloved teachers and mentors who toiled hard to make these course easy to handle.Gracious!
par Pedro J•
Feb 11, 2016
Since it is a very theoretical subject, trying to explain it without proofs and plenty of background is hard. But i feel like most of the course is just to memorize formulas without much explanation where they come from. A few examples are computing the expectation and mean of the average distribution and computing confidence intervals.
May 11, 2018
The course covers very important topics pretty well. The instructors knows the subject, materials are well chosen. However, the lectures could be done much better. There are many typos, the instructor is reading from the slights. Isn't it worth putting a little more effort since this course is taken by the thouthands of students?
par Gianluca M•
Oct 20, 2016
The course is good, but not very challenging. Anybody having done any course in statistic would have little to no information from the first two weeks. Only week 4 was interesting to me, dealing with boostrapping.
The teacher is very clear and chooses the subject in a clever way. One always understands what he or she is doing.
par Allister G A•
Nov 27, 2017
Brian Caffo is an interesting lecturer - he dives into the key concepts and ideas that are essential to understanding the statistical concepts necessary to gain a better appreciation of the course. However, presentation and materials need a LOT of work. They can be too overwhelming and most of the times feel irrelevant.
par Raul M•
Jan 16, 2019
This course should be targeted for Data Scientists, in my opinion it is more for statisticians.
Too much about the insight of statistics and some but not enough about how to use the statistic tools.
Some time the professor seems like he is just reading the slides which I think it doesn't intensive the student.
par Kirill K•
Sep 21, 2020
So in my opinion information that ws given in this course was not exlained well, lucky for me I was just refreshing these things, so I knew where I could lok for additional explanation. But if you don't have any background in this scope, it would be rather hard to understand why given formulas are working.
par Chadrick A E•
Feb 04, 2019
The course contains a lot I want to learn, but as someone with a limited background in statistics - I found many of the lectures not to provide clear explanations for concepts. I had to use a lot of outside material to try to learn and understand the concepts. The course lectures seem incomplete to me.
par Lei S•
Dec 28, 2017
The class contents are good I guess. But I don't think the professor knew how to teach and enjoyed the teaching process. Based on my experience, all the concepts are not that hard for everyone if they would be explained in a good way. I finished this course only because I want to do the course capstone.
par Robert K•
Jul 15, 2017
A good class, but I think there are some missing pieces. For example, there was a lecture on the basics of knitr, but nothing related to creating a pdf from R. In the Regression Models class there is a lecture on basic notation. I think it would have been more helpful to have that lecture in this class.
par Christian L L•
Mar 23, 2018
I really learned a lot in this course, but I find that I got most out of the lectures in week 3/4 when Brian actually stopped reading the slides out loud and explained the concepts i his own words. I believe the course could be improved by taking that approach in the other weeks
par Michael B•
Dec 13, 2017
The lectures are really hard to understand, while the material itself is really not that hard. The lecturer talks as if he is just reminding us everything we've already learned. Had to go to other MOOC (specifically Khan Academy) to obtain proper understanding of the topic.
Mar 07, 2016
The course was very dry compared to the other courses I have taken. Though there was a lot to cover in the four weeks but this was not best way to do it. The course covers a lot of concepts in far too little a time span. It should have been spread into at-least two modules.
par Pierre S•
Apr 11, 2017
To tackle such key concepts and tools of statistics, you need the appropriate time. Too much material covered in this course. I tend to think that revising the approach to this course as two 4 weeks modules would allow to both go more in depth at a more appropriate pace.
par Tamaz L•
Jun 20, 2017
ok course. They provide examples that make sense, although assignments don't really touch all of the material covered. The examples as well as assignments tend to be quite helpful, although I dislike how they force the specific format, which for some could be advantage.
par Jeremy S•
Feb 28, 2020
This is a decent overview of statistical inference techniques. Make sure you understand each lecture before moving on to the next since they build on each other. The lecture notes are decent but not great. I found it cleaner and easier to take my own notes.
par Eric J S•
Aug 06, 2019
This course was better than the others in the program because there was much less of a gap between the lectures and the graded sections in terms of expectations. Still, I knew this material going in and would not recommend this as a way to learn it.
par Christopher B•
Jan 03, 2017
It felt like there were a lot of jumps between basic statistical formulae and abstractions thereof. While I don't think it was inappropriate for a course on statistics in itself, it felt rather out of place in the rest of the sequence of this course.
Nov 29, 2016
The sections on bootstrapping and permutations were great! The instructor does much better, information is easier to follow (better and slower explanations), and the instructor is more engaging when he is not reading from his notes.
par Manuel M M•
Dec 20, 2019
The content of the course is really good and so the practices. But the teacher does not know how to explain things and easy subjects are transformed into a difficult ones. I had to study other books to really understand the subject
par Henk B•
Mar 30, 2020
Although the topic was very interesting, the way of teaching was troublesome. Teacher spoke often in a way as if he talked to specialists. So it was often hard to understand, and for understanding I needed to consult other sources
par Massimo M•
Feb 15, 2018
The subject of the course is very interesting and the professor is very competent. I had the feeling that some subjects were explained in a way that is not very convenient for someone coming from a non-statistical background.
par Jason M C•
Mar 28, 2016
The material in the class is solid, but is poorly described. These are the foundations of statistical analysis, and unfortunately there's a lot of statistics jargon that students aren't going to be familiar with in here.
par Richard M A•
Nov 28, 2016
Nicely outlined and broad in scope, but Brian's presentation is kind of dry. It often appears that he is reading off a script, and sometimes his emphasis on technical details takes away from ease of understanding.
par Fernando M•
Mar 02, 2016
I think the theory is too dense, but with a weak link with R. I understood better with swirl than with the videos. I'd suggest a more organized video with less draws and annotations. They confused me sometimes.
par Suman G•
Mar 31, 2018
Statistics & Probability being two of the toughest subjects, this course could have been taught a bit more novice friendly way, so that learners with no background in maths can also grab the lectures easily