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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 truly appreciate the great effort both instructors of this course have made to make such a dull subject as statistics sound more interesting. My impression is that this course doesn’t present any real intellectual barriers—everything is understandable when explained—but the knowledge fades quickly. This might be because the instructors didn’t explain complex concepts in the most effective way or help students quickly form memory anchors. Many issues were also not clearly addressed. I’ve had to rely heavily on extensive outside reading to clear up my confusion, and I often depend on AI to help me reinforce the highly complex, detailed, and easily confusable points. For someone who isn’t studying full time, this can be quite painful.

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.