was good but then has way too many mistakes

If you don't pay it you can't do anything

Very lenghty R labs to complete

Damn R-Lab

I found this course very very difficult with a complete lack of real learning support. The discussion forums are clearly not monitored, not even on a weekly basis, with dozens of posts dating back months and years that have not been responded to.

The course description was completely inaccurate in it's estimation of the time that would need to be spent to actually learn the content and do the weekly assessments. The content is great, and it covers a good range of basic statistics, but the teaching videos are so dense, I would have to watch each video at least twice, and spend time pausing and rewatching in order to take good notes. Often taking between 30mins and one hour for each video. I often had to search online on other platforms for better explanations of the content.

It was not made clear in any of the course information or introductions that we would need to learn a new piece of software in order to complete the course, and I think that for this basic level of statistics learning R is not an appropriate software. It involves coding and is too advanced.

The interaction between Coursera and the Datacamp platform where you learn R is poor. I wasted around 9 hours working my way through the first 5 chapters of R on Datacamp because there was no notification or mechanism to tell me that I had completed the introduction. It prompts you to carry on from one chapter to the next, and into the graded assignments without telling you that you have completed each section and that you should go back to the Coursera platform to learn new content before moving to the next chapter of R.

I only persisted with the course because I needed to complete it to get into a masters program and because it is cheap.

I wouldn't recommend it to anyone, and I will be sending feedback to my university to tell them to take it off their list of prerequisite options.

I did not enjoy this course. Although I appreciate ideas to try to make the subject matter more interesting, there were several things which lead to confusion: lack of use units in calculations; ambiguity in wording (this may be a 'lost in translation problem'); lack of formulae in handout; more complicated t-table than is necessary.

A ridiculous emphasis placed on the use of the coding programme and pre-requisite for completing coding exercises (not explained before signing up) rather than explaining the statistics with clarity. I cannot recommend this course and only completed it because I had nominated it as part of another programme so would have been too difficult to change.

I do not recommend this course for people wanting to understand the concepts with clarity. It was a real labour to get through. I found other resources more helpful in getting through the information so that I could complete the final exam and get the certificate.

Again, I cannot recommend this course.

The fact of aborting the subjects in a very fast and superficial way leaves something to be desired and ends up generating a lot of confusion both in the course and in the programming part. I would need more examples and activities so that knowledge could be absorbed more easily and intuitively. There are some calculation errors in the videos and the lack of some references associated with tables Z and T that generate a lot of doubts and confusion. Anyway, I expected the course to be more organized.

The information was amusing sometimes, but the first 2 chapters are sexist. That aside - the "R Lab" is not relevant to the class. Also, the order is backwards - all the interesting theory parts are the last 3 chapters!

It should be named 'Basic', or say that it doesn't require previous knowledge because it does.

That was the most terrible methodology ever seen in my life. I would stop it.

Very long and I was feeling unmotivated to complete the course

This course is really annoying since it asks me to launch R

i want to unenroll from the course, I am not able to do it.

terminologies overload on the first week of lecture

Tough