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 .
Mar 22, 2017
The strategy for model selection in multivariate environment should have been explained with an example. This will make the model selection process, interaction and its interpretation more clear.
创建者 Pinar T•
Jan 11, 2019
When you start statistics with practical examples, people tend to presume certain things (e.g. independence is given like in munchausen example) so I sort of understand this desire to keep every definition abstract/pure for solid foundations but damn, this course goes way too far. I took statistics at uni and this was a refresher on the specialisation track but the way Bayes' rule was covered made me doubt what I knew. Oh also, the instructor does some of my biggest pet peeves which are (1) using his preferred notations without actually reading it out loud first (2) unnecessary use of synonyms which just distract me from what he actually means (3) reading from slides without any context as to how these concepts are used.
Also, the concepts are elaborated on a seemingly random basis. Mean is left at "center of mass" like we just came out of physics 101 but the area under a curve is dragged out with random wood cutting analogies. I am just surprised at how all over the place this course is so far. Anyone starting from scratch, I highly recommend probability and statistics reading and some basic calculus elsewhere first. Otherwise you will get frustrated with this course.
Oct 22, 2018
This course is a fucking shitshow. Not only does Brian Caffo not explain anything, he has a tremendous gift to confuse people and make them forget / not understand anymore what they already knew. Great fucking course. Not. Hated it from the first minute.
创建者 Deshina B B•
Nov 27, 2018
The teach methods changed too drastically starting with this course. Much more prerequisite knowledge is required then is included int his concentration course set. No foundation or warning is given regarding this change and prerequisites. I had to seek out and spend countless hours on many other learning resources to get through this course and still don't understand what this course was trying to teach.
创建者 Rebecca K•
Sep 03, 2018
The information is so important and useful, but I found the presentation of the material to be fast and not very interesting, and therefore it was hard for me to retain the material. I learned a lot, but I would need to invest a lot more time to realllyyy grasp everything in the course. It wasn't presented in a way that made it easy to learn, so I need to spend more time going back over things to really get it.
创建者 Yusuf E•
May 21, 2018
At this point in the specialization, I was really worn out by the effort that I needed to put into this course (I solved the homework questions too). While I have no problem with the math, some topics like power should not even have been discussed or should have just been discussed in passing. Caffo spent a whole week on that. After taking the Applied Data Science in Python Specialization, I have a feeling like this course and Regression Models can just be merged, while logistics regression could just be transferred to the machine learning course.
Fortunately, the final assignment was very easy compared to the previous courses and one could finish it reasonably in a day (Reproducible Research final assignment itself took me almost a week) .
May 05, 2019
Not my favorite course in the series, but I did learn a lot. I highly recommend following along with the course book provided in the course. The videos alone are not enough. I also recommend printing out a sheet with statistical formulas to use (not provided from the course, but you can find easily on the web). The stat sheet with formula helped me connect all the dots and better understand when to use a formula.
创建者 Robert K•
Apr 16, 2019
A lot of material to cover - can be a strain, but well explained for the most part.
创建者 Don M•
Feb 01, 2019
This is an excellent course, though it is fast-paced. I didn't have time to watch the lectures and also do the practice exercises in Swirl in the time allotted. As usual, the time estimates for completion are wonky. I ended up just watching the lectures and taking the tests, which is far from ideal (I am taking some time to do those valuable exercises now that the course is done). Although I got 100% in the course, I felt the learning experience could have been better as a result.
Jan 29, 2019
Good Course to Learn the statistical Inference
创建者 Anthony M•
Sep 03, 2018
Poorly organized content and the lectures are presented in a confusing way. The lecturer obviously knows the material well, but is not able to present it well. He should use more sample problems annd examples. In addition, I am having trouble getting my submission graded, although I have already graded 6 fellow students.
创建者 Michael S•
Aug 26, 2018
The material is obviously invaluable but I thought the lectures themselves were lacking.
创建者 Dai Y•
Aug 16, 2018
There're lots of practice on manually construct statistics. I'm not sure if it's necessary to do that since we could just use R code to do it. I think how to interpret it and use these statistics in examples would be more important. There're some examples, but could be more and interpret more in depth if there were less focus on the calculation.
创建者 Mingda W•
Jun 05, 2018
My most recent experience with statistics was about 2 years ago, and it was college level statistics. Still, I find this class is hard to keep up sometimes. In general, I felt like the professor explaining too much on the mathematical meaning behind equations instead of talking about the real-world meaning of equation components, and why those calculation make sense.
Jul 21, 2017
I couldn't make it through this course because I can't stand looking at the instructor's face on the screen. It is very distracting. He is also not very clear in his whiteboard explanations, too much scribbling. I prefer courses taught by Roger Peng.
创建者 Stephen G•
Oct 25, 2016
The only reason for enrolling is to complete the data science specialization, though it may make you reconsider continuing with it. The instructor and provided materials fail to adequately explain the concepts this course is supposed to cover, and do not prepare students for the quizzes or assignments. If you don't know statistics you won't learn it here. If you know statistics, you don't need this course.
创建者 Joshua A B•
May 29, 2016
I've taken several statistics, data science, and R courses. This is one of the worst. I took others' advice, and I also strongly suggest looking to other sources to learn Statistical Inference before taking this course. Khan Academy, DataCamp, Udacity, Duke (Coursera), and Columbia (edX) all have great courses. Though they vary in depth, each leaves you with a good understanding of the concepts they teach.
创建者 Yohan A H•
Jul 10, 2019
The topics are very interesting and there is no dude that the teacher knows wath he is teaching, even though I think it can be better with more grapics splanations and less formulas.
创建者 MEKIE Y R K•
Jul 08, 2019
Really Important course
创建者 Mukarram M•
Jun 29, 2019
The worst teacher ever!
创建者 Chunyue Z•
Jun 16, 2019
The materials are not so clear to someone who's not familiar with stat.
创建者 Rok B•
Jun 10, 2019
Great course! Gives a really nice and comprehensive overview of basic statistics
创建者 Jorge B S•
Jun 03, 2019
Very nice introductory course to statistical inference concepts using R.
创建者 Pranay R•
Jun 03, 2019
A very conceptual course to understand the fundamentals of Inferential Statistics. I would recommend this course to all aspiring data analysts/scientists or business analysts.
创建者 Marcus H Y T•
Jun 02, 2019
Concepts are not well explained and slides are not well prepared. Last few topics are too brief to be useful.
创建者 Charles M•
May 27, 2019
Elegant presentation materials and contains evaluation materials that target essential concepts and learner's ability to apply course information. Very well done and looking to take the biostatistics bootcampe alluded to in the lectures, by the same professor (Caffo).