Brilliant professor, lectures were clearly and nicely explained, and quizzes and exercises are really well thought-through to stimulate learning. Great course!

Learned so much from this course, and with just this alone, I was able to create my first project using R.

Excelent Course!! Thanks a lot Dr. Mine Centikaya, you are an excellent professor.

very helpful and easy to learn

It's a great course!

thank you

Thank you!

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Great intro to basic statistical inference theory for the foundational use cases (means, pairs, props, chi-square, etc.). Helpful R labs to build basic programming and statistical analysis skills, as well. My one main critique is that the course doesn't seem to be actively monitored by Duke or Coursera, so getting feedback or help from a professional source is pretty much impossible. The course is well-designed to be self-explanatory and you can certainly complete it successfully on your own, but just keep in mind that there will be no help active help from an instructor or staff member.

Really useful course

I'm beginner at both R and statistics but It wasn't so hard to understand concepts

but it seems that professors or TAs don't really care about this course.

1. one RMD file was expried so that i couldn't kint document

2. almost no TA's answers for questions on discussion fourm

Well-taught, but they need to provide more resources to help people learn R. R is not a user-friendly app and I needed to google how to do a lot of the things they're asking us to do. Needless to say, I can google how to work in R on my own without paying Coursera a fee.

The course factually do not teach r. It's much longer than it was declared. The core statistical course is quite good, but information about computer simulation methods looks like was entered retroactively

some topics require more explanation!

This is an interesting course, but the textbook it uses is outdated by a newer edition, and classes / readings should be adjusted to reference the latest publication. The professor's videos explain statistics very well, but there was really very minimal discussion of R and R Studio in the videos themselves. The weekly labs went over a few R-based scenarios, but did not provide enough examples or a broad enough overview to prepare students to use the program effectively if they were not already familiar with the program. I struggled to try to use R to answer some questions posed by the labs, and there was no real support in the discussion forums to help me figure out where I was going wrong with my commands.

I think that as a stand alone course, if R is going to be tested it probably needs a R teaching module. At the beginning of the course definitions and key words need to be identified better, in weeks 3/4 this was dine very well. But should be front loaded for obvious reasons. I also think utilizing one statistic set or "situation" frequently would be better when possible so thay learners can understand how the numbers and concepts are changing. But overall very effective course!

The course is interesting, the instructor competent and you can learn a lot when you also buy the book. Unfortunately the course is a few years old and the materials have not been updated since then. Code samples don't work anymore, links for material or quiz don't exist, references to the book are outdated (sometimes a wrong page, sometimes a wrong version), questions in forum are not more answered, and so on. If the course would be updated, i would rate it 5 stars.

It was good. But I feel like I've spent half of the time untangling sly phrasing of questions.

I should not be charged if I have completed the project and simply waiting for other users to review it. This is dependent on how many users are taking the course at any given time. A bad system that results in users paying more for uncontrollable uncertain factors...

As with the previous course in this specialization, the statistics instruction is quite good. The R instruction is almost non-existent. You can expect to spend plenty of time on your own, Googling the skills you'll need to complete your end project.

The course was not very helpful for me, as practical cases with R were poorly developed and the final data capstone project is badly formulated which makes it extremely difficult to pass.

Lots of perplexing questions in their assignments, and the quizzes were too difficult. However, I garnered modest skills in this program.

I would only recommend this course to someone who has learnt the syntax in R and is looking to apply it for statistical inferences. Though the concepts are taught well and clearly, it should have been mentioned that the prerequsite for this specialization is knowning how to code in R because i took this cause thinking it was going to teach me R alongside statistics, and combining the two. Even so, not much programming in R was done which was quite disappointing to me. I would highly recommend learning R on youtube or taking a beginner course on Udemy first before attending this, which was what I did.

Not able to grasp even a single concept. For every topic I've to go to youtube to study it. The instructor seems to read a page. There is a difference between teaching and reading

can't finish the final project as the link to data is no longer available.

Professor Mine is terrific. I'm sure she has a great depth of knowledge and grateful that she's able to deliver her knowledge out to listeners. She uses meaningful examples all along the course, no dry pure mathematical cases at all. That helps a ton to digest concepts. And she constantly repeat some core concepts and how to interpret a statistic right. I didn't realize how important this was until I was challenged with questions, then I came back and hear again her interpretation, and the whole thing became clearer. She's one of the best professors I've ever listened to, and I've been through grad school, met so many professors.

The current mentor Rolf was great at supporting. He answers a lot of questions in the forum. He's very responsible and supportive. So if you're considering on taking this course, take it now as mentor will change!

I haven't finished the course yet, but the enrollment rate seems to be quite decent, so I wouldn't expect it to take too long to get final project reviewed and get certificate. I assume this is an important issue for any course takers.

The only downside is that there could be more R code teaching, especially on complicated simulations. That way it may be more friendly to R beginners. I know it's important to do research ourselves for codes, but beginners could lack of proper terminology or vision by nature to do the research on Google. Especially when I'm physically in the Main Land of China, where it takes some efforts to even get on Google, so doing code research took a lot of my time and was a little frustrating towards the end.

But again, the overall course and support are great! If this is not a 5 start course, I can hardly give out my highest mark to any other courses. It helped me to understand inferencial statistics, practice R, and think more like a statistician.