I'm in the data science specialization. Statistical Inference was my 6th course. All of them have been on a spectrum of good to great. But Statistical Inference is a mixed bag for me.

First, if you are thinking about this course, take some time reading the other reviews. I find many of them resonate with my experience leading to 1/5 stars.

One reviewer who gave 5/5 stars said they loved the course. They suggested that other reviewers who gave low ratings are ones that dropped out. I don't find this to be the case. Many of the low rating reviewers actually did pass the course and said very similar things as those who did not pass the course.

Another reviewer enjoyed Brian's dry humour. I must have missed the jokes after watching each video 5 times...

For the record, I almost aced this course. The reason for not getting 100% was because I was so annoyed with one of the quizes that I didn't bother taking it again to correct it. I decided living with 8/10 correct questions was better than having a stroke while in the pursuit of two extra points. Yes, that is how much I hated this course.

The first 2 weeks of the course were the worst. I dropped out for about a month (because of life priorities). Then I couldn't get motivated. 1 month turned into 2 months, then into 3 months. I basically took the entire summer off. Finally I bit the bullet and completed the final 2 weeks. The 3rd week of the course wasn't actually all that bad (though the quiz was terrible). The 4th week felt like the first 2 weeks...terrible.

(By the way, it's a mistake to take such a long break. I had to re-watch the first videos to recall things for the remaining quizzes).

If you don't have some sort of statistical knowledge (or inherent aptitude), be prepared to work four times longer on the course. For all your quiz and assignment time-to-completion estimates, multiply them by 4 or more. Seriously, I spent probably 10 hours on the final assignment which said it should only take 2 hours. Each quiz took me an entire Sunday afternoon (My partner was not pleased).

Now here is where things get awkward. I hated the course .... BUT....I learned things that actually stuck. So in THAT regard, I give this course extra stars. It accomplished something that some University courses could not. I even found myself USING the new knowledge in real world problems. So ironically, is that not a sign that it's ...dare I say...a GOOD course?

Would I take the course again? I actually might, but ONLY because of its place in the overall certification. If you are a prospective student wondering if you should take the course as a standalone course, I don't think I could recommend it, because there are far better ways to learn. In fact, just doing the Swirl lessons could be good enough.

If you are a prospective student and you want the certification, then you'll HAVE to take the course. Why are you even bothering to read reviews?

So I'm giving the course 3/5 stars. If I gave it 1 or 2 stars, my review would be clustered with the majority. If I gave it 4 or 5 stars, I'd be lying.

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.

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.

I found the lectures hard to follow, they didn't help me one bit. If you get his book, read it, and do the exercises, you can save yourself some time.

The materials offered from this course is far away enough from understand the content :(

A lot of material to cover - can be a strain, but well explained for the most part.

Very fast course... Additional reading required.

I am left feeling this course needs work. I don't know if it's the pain of switching to the new platform or what, but the total lack of any support from the TA/instructor team is frustrating. Add to that the fact that Brian skips from slide to slide very quickly often not providing adequate explanations and you'll be re-watching the videos many times over.

Several of the videos have blatant errors in them, like the fast that the fourth video of a week also contains the entire third video... again.

Such things should not have passed a half decent QA test.

More than anything this specialization should not be marketed as "no previous experience needed". You need to know some statistics. And by some, I mean do the whole thing on Khan Academy first.

The content of the course was well organized and structured, but the content delivery in the videos was terrible. I was unable to understand even the basic concepts from the professor due to his fragmented sentence structure, lack of lecture planning and an emphasis on evaluating R code more than on explaining the concept. I am now hesitant to go on to the next course in this specialization. The Swirl() exercises, however, were very thorough and did a good job in explaining the concepts.

This course was very hard to complete. The lectures were harder to follow than the previous courses.

Wouldn't recommend for those learning stats. Try Duke's course instead. This one was poorly taught.

The most boring and nonsense course I have on the Coursera so far. I have a PhD degree in Stem, and had taken statistics courses during my undergraduate, and also had some teaching experience. I can't believe they can made a course like this quality. It downgrades the reputation of the department of biostatistics at the JHU. I saw some criticizing comments before I took the course, but I thought it would be OK and I would get through it. But after taking two weeks' courses, I just feel so frustrated and furious and can't help to write down my comments.

The format of this course is like, first, read out the parameter, and then read out the notation, without giving any explanation about how to calculate this out, why we want to introduce this parameter, and how we use this parameter. And then the instructor gives an example, but I don't see any of the examples emphasize the notions.

I just can't help to write down my comments. I don't want to give even one star to this course!!!!! Such a shame.

There should be some teaching centers at the JHU where some teaching professionals can help to improve the structure of these courses and give instructions about how to deliver the contents organically. I beg you to have some improvements.

I hate this course. The instructor's way of explaining things was not that good. Could not understand most of the concepts.

This course was

very, very, very disappointing to me. It were hard to complete, hard to follow the slides. Wouldn't recommend for those learning stats.

A lot of the concepts, although simple when you think about it and used pretty much every day, I felt it were really difficult to understand at first. Wikipedia and some other online sources, and youtube videos, were more helpful but I think the real issue lay in the teaching style.

Brian seemed a very intelligent person, but he does not teach well. His way of explaining things was really bad: he speaks too fast (sometimes he changes terms...), he skips from slide to slide very quickly, he often do not provide adequate explanations.

The lessons require intermediate level in statistics and it is a complete waste of time watching the videos without doing an initial course of statistics. Thereby, It requires much more time than expected to learn the topic, which includes reviewing basic concepts and doing the (optional) assignments. Moreover, the questions in all quizzes are more than challenging very tricky.

The course is poorly laid out and the concepts are poorly explained. You'll need either previous college level statistics courses or be willing to spend a lot of time outside of the class to understand what's being taught. The quizzes have little to do with what is presented in the lecture. Unless you are going for the data science certificate, I would look some place else.

The lecturer is talking way too fast, simply reads off the slides and doesn't dive deep into any of the concepts behind all those definitions. You won't learn anything new here! So stay away from this course if you don't really need it for the Data Science specialization. There are way better alternatives even on Coursera (e.g. Inferential Statistics by Duke University)

Los ejercicios están completamente desactualizados y no corren con versiones actuales de los programas. Es necesario que den mantenimiento a este curso, ya que los últimos comentarios que se respondieron por parte de los instructores, lo hicieron hace más de dos años.

The course is very monotonic and confusing. The lecturer literally reads the notes quickly without trying to connect to the students. It seems that the teacher is in rush to finish the video.

I do not recommend this course and I think it's a waste of time and money!

Not designed for people without good Stats knowledge. Formulae thrown onto the page at blistering speed. Terms and notations used that have not been defined. Course book pretty poor. I had to do another stats course elsewhere to have any chance of taking it in.

There is a lot of theory in the course but it is not always treated with the necessary rigorousness; this creates confusion and makes it difficult to understand the basic concepts.

I don't find the button to leave the course!!!!

I learned so much from this course. Brian has an occasional irreverence and dry wit that keep things lively. I will say that I disagree with some of his interpretations, but this is OK!

I would like to see some integration of type s errors, capture intervals, and all the other things the cool kids are doing nowadays.

I am now taking Bayesian statistics online via Richard McElreath's course and this one does help a bit in understanding likelihood functions.

I thought most of the lessons in this lecture were enjoyable, since it went into the theory of decision-making from data. I feel you need to take an introduction to statistics course before taking this course though, since the lecturer goes too fast at times. I recommend Udacity's Intro to Statistics course, as it helped me understanding the lectures in this course. A+ material though in my opinion.

This course is one of the most difficult to comprehend, particularly if one does not have any prior knowledge of statistics and probability. But Swirl package of Statistical Inference helps a lot and is a good heuristic approach to learn.

P.S. I would recommend to read this lecture along with any textbook. I referred Probability and Statistics (Schaum Series).

I absolutely loved this course and felt like i learned a lot about statistics. This was very informative and the peer graded assignment was a perfect way to conclude the course, by having to perform all of the phases in Data Science that I learned by taking other courses in this series. Thank you for this course! Looking forward to the next set of courses.