Even though I graded 5 stars, I would actually prefer to grade 4,5 stars this course. I liked many things, but some were really frustrating. Pros: the overall knowledge that is offered in this course (BA level), course structure, quizzes. Many students critized the course integration with R, but I do like this fact. I am aware they could have organized the practical part with some other tools, but for me R is a necessity and a must. However, there are some drawbacks. 1. The presentation quality between two instructors was noticeable. Somehow, one of them was repeating more, had a slower pace, more vivid examples, which I prefer. 2. There are several important mistakes with numbers in the presentation slides. Many students have already noticed that, so it's a pitty no one corrected them. 3. This drawback is more for DataCamp, and not for this course, but the spelling was really bad. Too many obvious mistakes. 4. Final test. It was quite demanding for me. I still don't know how one could answer 30 math questions, many of which include calculating, for only 1 hour of time!? Also, some questions were really tough and I haven't found an answer anywhere in my lectures. There are at least 3 answers that I don't know how to explain why were (in)correct.

I plan to take another statistics course in Coursera, as well as at Khan Academy, so I will be able to compare and evaluate more adequately the knowledge presented. For the time being, I would recommend this course!

Very clear course. It really started with the basics, so I could understand everything. The set-up (transcripts with videos, helpful animations in the videos, R labs, quizzes) was really designed to get the most out of it. I learned a lot from it.

Two points of approvement:

1) Feedback on the quizzes! I thought it was really a loss that I couldn't see what I did wrong in the quiz (you can see which questions were wrong, but not which answer you chose and which was the right one) and that there was no explanation of why the answer was wrong. This way, I learned nothing from my mistakes in the quizzes, unfortunetely.

2) Quizzes took me way more time than what was designated for them, because some of the questions had to be answered in R or manually, and the course didn't teach me a quick way to calculate the answer (or sometimes it did, but the small data sets given in the quizzes aren't implemented in R so doing this manually also took quite some time). This way, a simple multiple-choice question could consume way to much work because you sometimes had to do a lot of tedious manual work.

This is a good course, and I would recommend it to anyone who needs an introduction to statistics. My main criticism is that now that the course is up and running, nobody seems to care much about maintenance. Some of the lectures and R-labs have mistakes in them. I understand that you cannot redo the videos, but it would be extremely helpful if you would create a printable document containing all identified errors, that students can check while watching the videos or doing the labs. Expecting students to go through years of postings on the forum to figure out if they misunderstood something or whether there was an error in the materials is unrealistic. It would also decrease the workload of tutors that receive the same questions over and over again. On that note, while some questions in the forum get answered very quickly, others remain unanswered for months.

In my opinion this course is a good way to learn basic statistics. I do think the R part and the statistics part could be more integrated in order to learn R better and to use it more efficiently. For me the studytime was double the time that was stated even though I was already familiar with some of the concepts and calculations. I feel like some weeks the subjects should have gotten a little more explanation with video's or other supportive material, maybe some assigments to make in order to check wether you know and understand the material. Maybe you could compare content and way of teaching to the Duke University statistics course, this is not a better course per se but does do some things differently whilst both teaching stats and R.

I think the course content is very good. The videos are done really well. The videos are so good that they made me lazy with making notes. I could fairly easily recall the video content for the weekly quiz, so I didn't make notes. But with the exam I couldn't remember everything that we've done several weeks ago. So I had to look-up the rules and formulas in the transcripts. But, I think the transcripts should show the formulas. If the formulas were in the transcripts, it would be much quicker to find the relevant information and apply it to the problem. Or maybe provide a course summary / text book, which makes it easy to determine what the name of a variable is, when to use t-score or z-score, etc.

Much better than the Univ. of Ohio introduction to Python e-course. The lecturers are more interesting and better produced. Likewise, the r course is better structured with more questions that build upon one another.

Down side: a lot of spelling mistakes, particularly in the r package portion. Also, some of the r questions were not intuitive, even after seeing the clues and/or answers. Finally, I still don't feel very competent at applying various formulas or the reasoning behind some of the statistical measures. I think the course would be better with some practical coding examples and examples after each lecturer video instead of all grouped up at the end of each week.

I genuinely enjoyed this class and learned a lot, but it was difficult and very time-consuming. I spent hours and hours on it. I just spent a total of around 7 hours on the final exam and still managed to fail it the first time. If your strengths don't lie in numbers (and apparently, mine don't), expect to spend more time on this course than on others. The lows are lower in this course than in other courses in this series (frustration), but the highs are definitely higher in this course than in the others (greater feelings of accomplishment when you finally figure something out). I also loved/hated learning R and I think you will, too. In the end, I think it's worth it.

The videos from the first professor were amazing and the examples he gave were very important to better my understanding of when/how to use the equations. The use of R was nice but not necessary at all and it hindered my understanding of the course. I wish there would have been more work in the videos with how to use R and then work with it after. In R, the "hints" were not always good hints or had anything to do with the scenario and it became increasingly frustrating to use R with no experience and it did not seem to help with my understanding of statistics at all.

Overall it is a good course with the professors explaining many concepts through real world simple examples. But, sometimes I felt some videos needed more explanations. Again, I wish the answers to exams in feedback had more precise explanations. Whenever I felt something was not fully understood, I tried learning with other online resources.(like Khan academy AP Statistics course has lots of maths problems which make the concepts more clear). Again, one of the biggest drawback of this course is that it lacks handouts. Hence, always make notes while studying.

This course has given me a much better understanding of many concepts I never understood while studying at university - Like the sampling distribution etc. and I can recommend it...

The only "but" is... I can see from the discussions that some (many?) students have problems with the "R" assignments. I have been programming previously, so I have not have had these problems. I would though like that these "R" assignments where easier to print or collect in a PDF document, so that I could easily use it as a "howto" later.

The course is good and will suite the most. I had some previous experiences with statistics (almost forgotten) and this course was a good way to remember the old stuff and take something new.

Material is clearly organized and the teachers did a nice job.

The only thing is that several times I had a feeling that the material in the course is not completely consistent with tasks in R, plus a couple of confusions in the course itself. However, possible to solve yourself if you listen carefully and enjoy your learning.

It was my first experience with statistics, so some parts were not easy, especially when it came to probabilities, to understand material I needed to look for explanation in the net, course materials, unfortunately, were not enough. Still, this course is great, tests are good opportunity to exercise theoretical concepts and you can try until you get desired result. R labs were a real challenge at first, since I didn't have any programming experience, but now I can say proudly that I can do something in R :)

Professor Roodijun explanations and R-labs were much more than those from the other professor, but the lack of practice problems in all of the lessons was a real drawback. Even if the practice set was ungraded and optional, they would be highly beneficial to help internalize the concepts. At present, the only chance to practice is on the graded quizzes at the end of the lessons, and those quizzes cover the entire lesson, not the individual skills we are learning along the way.

Very demanding Course Well- organised material Brialliant theory, very helpful for everyone learner. Variety of examples in order to learn better the theoryDemanding also assigments and quiz,You need so many hours of studying in order to complete it successfully escpecially if you are not familiar and experienced with Statistics and mathematics. But of course i will reccomend in everyone who want to gain knowledge to this domain. Well done to all! Thank you about this basis.

Certain lecture videos, especially those of Professor Van Loon, can be confusing and unclear (though I'm not saying it's his fault necessarily), and there are certain errors throughout, but overall this course is relatively engaging and effective at giving you the basics of Stat. As someone with almost no prior knowledge and a terrible historic ability at math, I passed easily by watching the lectures, taking detailed notes, and spending time with the labs.

I was so excited about this course and really feel like it was well worth my time and effort. I have to say though that the labs in DataCamp didn't line up so well with the weekly assignments. Learning r while also learning statistical theory and formulas is difficult to keep things straight (for some of us anyway). I am very glad to have the intro to r, but I think it could be structured differently. Also, please include more exercises to work through!

The videos were interesting and well-presented. I do not have a background in statistics, so the pace of formulas and calculations was tough. I'm not sure if there is a place where remedial folks like me can get a slower pace of basic stats and the maths involved. Having that foundation would have made this more understandable for me. The R-lab was interesting, but I quickly got lost & learned a lot from all of my wrong answer lol.

I had a really great time with this course. A lot of work went into it, from the presentation to the content. Really well done. It was quite challenging. I felt that the last module (7) introduced some very difficult concepts which, even after checking other sources, I couldn't understand fully. Some questions from the exam in that module were substantially different from the ones in the lectures. I would give 4.5 stars if I could.

I liked the content of the course very much; the videos were all very clear, with nice examples & visualisations of those examples. However, the R labs included in this course were not very challenging; by following a list of steps you can complete them easily without learning much from them. Additionally, the R labs sometimes would not accept an answer as correct when it was a slightly different solution to the same problem.

This is a good course for the videos (some mistakes there, beware) and material provided, but it is just ok as the quality of the tests. Sometime just felt like a monkey typing again the same ops over and over. The R lab is sometimes really frustrating as questions are not clear enough. I feel a good table of Z and T scores for the most used confidence and significance levels would be a good addition to the course material.

Lectures and quizzes were great. The main part of the course was fun and informative.

Labs were awful. They did not teach or incorporate R well, they were inconsistent with the way answers should be provided, and instructions were very often unclear or missing information so that the answers could not be obtained without hitting solution or googling r things that had not been brought up before.

Overall a very good course; excellent, easy to understand explanations and engaging instruction. However, there are a couple of places where the course needs a correction, and I am deducting a star because it has been up for literally YEARS, and no corrections have ever been made. If they would actually correct the few course errors, it would be an absolutely perfect course. Cheers!

Perfect for gaining a general/ beginner knowledge, but still in-depth and good quality. As a complete novice with no natural flare for maths it did take me a lot longer than the predicted times, and I did feel like you had to research further or work around what was given, in order to answer some questions in the exams. Overall, really helpful to get the basics of statistics!

Thanks for preparing this course. All materials can be useful for anyone who wants to do statistical analysis in any fields of expertise. However, I think focusing more on practical statistics can be an insightful idea for teaching statistics since it would make more sense for all students to use these concepts and knowledge to solve scientific problems.

covers a lot of topics in a very simple manner. liked the examples taken in the course and how the important points in hypothesis testing are stressed.

the course can be improved by maybe making it a little bit more mathematical.. giving some proofs(which if the course coordinator thinks can be done in the time limits) to the formulas used in the course.