Uses R with no explanation. Why does it use a challenging programming language that is not the point. The point is to learn statistics.

Use Statcrunch - so students can focus on statistics not programming

Finally, I notice this course extremely useful for people who haven't got abundant background in statistics. The lecturers and illustrators have done a awfully sensible job explaining arduous ideas through fun examples. Some flaws i would wish to mention: The the discussion forum isn't terribly feverish, and in some weeks, sounds like associate degree abandoned island. The course has not provided learners with comfortable materials, like commonplace z-table, t-table, etc. many ideas aren't completely explained (the P-value, for example), maybe because of their toughness, therefore sensible articles with elaborate rationalization on these ideas would be an excellent addition. and eventually, whereas assignment queries ar sensible and comprehensive generally, a number of them want modification to avoid ambiguity (by adding info regarding whether or not they ar considering one-tailed or two-tailed check or providing z-score employed in the question, etc) for learners.

I got to know about this course as it was a prerequisite for a MS in Business Analytics program I will be joining this Fall. I do have some background in this subject due to a previous masters degree, as well as work experience, but this course was an extremely helpful refresher of the basic concepts that one needs to know. What I liked most about this course was the crisp explanations provided in the instructional videos; without taking too much time in delivering the required message. I also liked the fact that the quizzes focused more on testing the understanding of the concept rather than expecting me to perform complicated multi-page calculations. Would recommend this as a very useful starting point for others like me. It would be helpful if some kind of a diagnostic exam was added at the start of the course so that students of different backgrounds could assess if they're ready for the course or not.

Amazing course! I have learned more about statistics in this course than in my entire bachelor's and research practice. Some weeks (3,4 and 7) are a bit difficult and poorly explained: brace yourselves. Also, the R Labs are really helpful if your are interested in learning R programming as well. I've learned so much in this course (and in the other courses of this specialization) and this knowledge will be really useful when I start my research masters next fall.

If it's useful for someone: I completed this course in 3 weeks, because I'm in quarantine, so I'm not doing much work related tasks (covid-19 present here!)

The videos are phenomenal! Thanks for such a creative and thorough course.

My one recommendation for improvement - some of the formulas for different parameters were different between the course videos and the R environment in Datacamp. This led to some confusion.

It is a great course, I learned a lot but some recommendations.

The teachers should revisit some R classes, I found some typos and specially week 7 R Class, since most of the class are problems based on the videoclasses but more advanced, getting together topics already taught in a more difficult way, a class about all that is recommended, I understood almost nothing and it was more like guessing.

Some exams need extra explanation of the reasons why an answer is wrong or why the right answer is the correct one.

Overall, very good course. I thought the weakest sections were the ones taught by Prof. Emiel van Loon (the dark-haired one). I found him much less clear and engaging than Prof. Matthijs Roduijn (the blonde one). The R labs were fine for me because I have a background in programming, but people without that may need a lot of time to do them.

I recommend this course for people like me, who has learned some statistitcs but find them kind of difficult to understand. Matthijs Rooduijn explained his classes pretty clear and I understood a lot more thanks to him. Emiel van Loon tried to explained the two modules of probabilities, and in my opinion it´s really hard to follow his explanations, you need a lot of patience for his two weeks.

In general, the course is pretty nice. I like the R lab exercises in DataCamp and you can check your mistakes on all quices and try them once again, what allows you to learn well.

I give 3 stars because, besides all the good stuff, the course has some mistakes on different exercises (in both quices and R labs). And the course doesn´t have mentors right now, or anyone to whom you can scream if you don´t undestand something. My personal recommendation is to do this course with someone else if you aren´t autodidactic, and have a lot of patience when a exercise is marked as wrong.

I was really enjoying this course in the first week and then I realised I had to switch from statistics to programming before moving on. I am doing other courses and needed to get my head around statistics so decided to enrol in this.

Then I realised we cant progress unless we learn R. Learning programming and statistical theory are two different things and I found the R lab very confusing.

Very disapointed will now have to look for another statistic course.

I just wanted to learn statistics, not also learn R, which has made completing this course impossible!

Good lectures, but the R-lab is horrible. Do not take this class.

Definitely a solid introduction to statistics- I found that the course was broken down into nice, digestible chunks where every lecture consisted of explaining a single topic over 4-10 minutes that would be built on over the course of every module. The quality of the videos is good, and the lecturers do a good job of explaining the concepts in a clear and concise manner.

I invested easily twice (if not more) the stated weekly study time in order to internalize the concepts being presented in the course, and I would highly recommend others do the same if they want to get the most out of the course.

The only thing I missed were perhaps further practice exercises with solutions, beyond those covered in the lecture or practicals. That would be the only neutral point in an otherwise very good course!

I really loved this course. I sat down for a week or so and dedicated myself to completing it, and I learnt a ridiculous amount from it. The videos are clear, and cover a wide range of areas within statistics. As long as you focus, and dedicate time to properly pay attention, write notes, give their examples a go before continuing the video, and to learn where you went wrong, you will find this course very useful! Though some videos seem like they could be more concise, their explanations and examples have allowed me to vividly picture the different concepts, and remember them! (ALSO) To be able to learn the basics of a programming language in such a short amount of time is great, and the labs really allow you to revise over the week's topics.

This is by far the best course I have done on Coursera. The syllabus covered is very relevant and the tests and assignments are challenging and fun. I want to thank both professors and the supporting team for developing such a great course. Thank you!

This is an incredible curse. It has a lot of information, but they manage to deliver it in a dynamic, fun, and quite intuitive way, so it is really easy to develop an inner logic for all of the statistical concepts. Thank you very much.

The Content was really hard for a non English speaker. There were times where I couldn't clearly understand what was asked. Also the Datacamp Exarsises don't promp you when you need to stop before the next lesson.

This is a nice course...thanks for providing such a great content from University of Amserdam.

Please allow us to complete the course as I have to wait till the session starts for week 2 lessions.

Brilliant material and the professors are amazing! I thoroughly enjoyed the course and would rate it 100% easy to understand , difficult concepts explained clearly, lots of exercises

Excellent for understanding the basic concepts and designed for those who have no clue what R is..

This is great! Every single concept is explained in avery easy and intuitive way! I loved it!

Excelente curso. Muito didático e divertido.

Thanks for a great course. I really learned a lot. I came away with what I wanted: a basic grasp of key concepts in statistics that previously I had merely a superficial understanding of -- standard deviation, confidence interval, Pearson's r, etc. The video lectures were fantastic: clear, engaging, fun. I liked that I could pause them when I was confused on a point. A couple of criticisms, though. First, I found the r program frustrating at times. Sometimes it was used in a way that helped me to better understand the course's key ideas. But too often it was an exercise in guessing the obscure programing code to use. Since I'm unlikely to ever use the program again (and I suspect this is true of most students), overall I found the r programming of limited value. The other drawback of the course -- not your fault! -- was the same problem with all on-line courses. At times, I just wanted to ask a question or get a clarification on a point, but that just wan't an option. Finally, I think it would have been helpful had you provided an in-depth explanation of how to arrive at the correct answer for each question on the quizzes. For the quizzes, I was usually able to figure out the right answer (eventually), but not so for the final, which didn't provide any explanation as to why I got certain questions wrong. But, as I said, overall this was very good course. I got my money's worth.

I love the vivid examples, and the all the visual explanations. They really helped with understanding the concepts. The assignments and the R exercises are well designed and align perfectly with the course content which helps as well.

Meanwhile I wish there was more explanation about the math behind the formulas (as to how those formulas were derived) instead of just teaching us how to put numbers into those formulas. That way we'd be able to better understand the "why" behind the fascinating data behaviors. For instance why do we say when n >= 30 then the sampling distribution of sample mean is normally distributed? Why when number of success >= 15 and number of failures >=15 then the sampling distribution of sample proportion is normally distributed? What are the actual reasons behind using t-table instead of z-table when we do not know the population σ? Just a couple examples off the top of my head.

This course was great to get an introduction of basic statistics and inferential statistics. The R exercises are great to test what you learned with practical exercises (in a real-life scenario where you have access to a tool like R). I cannot give 5 stars, because the chapters on probability are confusing and poorly explained: probabilities are one of the most difficult parts of statistics, so they require more pedagogy (with clear formulas to calculate conditional probabilities and step by step explanations)

The probability section was super hard and not terribly well explained. I had to get help from my statistician friends in order to pass the probability density quiz and it was remarkably frustrating. Everything else was really good though. I like using R too, it's quite intuitive :)