Very nice

good work

amazing!

Perfect!

Amazing.

EXCELENT

good.

great

great

good

:)

C

/

Thank you for your course. Teaching statistics to the ones (majority) who do not have maths background is incredibly hard and the works for teacher is humongous. Few flaws to highlight: some parts where a little bit too "simplistic" like for instance; sampling and frequency distribution , ANOVA Z and T tables. These parts I believe requires a little bit more insight in the nature of the maths behind it to grab a better understanding of it. I have to say I had to integrate your material with other you tube videos on the web to get a deeper sense of it. An introduction to ROC curve and Meta-analysis is something to consider for future courses

I have also noted a lack of reply to many questions written on the Forum.

But overall a very good course which delivers basic concept of statistics. I think I have improved the ability to better understand the methodology behind research and research manuscript.

You get understanding about basic statistics in biomedical reasearch but not deep. If you will to know how to perform the tests either by problem-solving and getting to know how to develop those calulations in each case for each test, you might have to further study in other places. I wish it also had that possibility with learning how to process the data for those test in informatics programs too such as R. I expected to learn from this course how to apply that knowledge (which was great taught) to my own research to produce conclusions over my trials

Overall, very nice explained and you get to learn a lot about data types and analyses. Now I will be able to understand what statistics is telling me in researching papers although I will not know how they did the maths underneath or how to apply it to my own research. I guess this is a first step ans basic knowledge was gathered here

Such a great course!. Although it is most suitable for persons with some expereince in clinical research and/or stastics, persons from other career backgrounds can cope and will find the course illumating. The content is rich and has been designed to appeal to participants from a wide range of backgrounds. However, more visual illutrations could be addded to the course material as the course presentation commentary was overly verbose at places. Nonetheless, as a person with a background in law and who had never had anything to do with clinical research prior to taking this course, I can say that this was a valuable course.

I'm thankful for the fact that there is little mathematical detail about the statistics, which is indeed a good choice for anyone who just want to correctly "read" a clinical research. The knowledge of the last 3 weeks is, however, too concise. I would love know more about story/nature behind each test, or at least, some good material too read or listen to. But I think, the course is very well structured, lectures are short and clear, examples are interesting and practical.

I found this course very helpful in breaking down the subject matter well and making it easy to understand. I however think there can be improvement in terms of the manner in which the information is conveyed in the videos. They should be made more exciting and more images and graphs should be used to help the student understand, not just the lecturer speaking. I also found the readings rather redundant as all they information was already relayed in the video before.

I found this course very intuitive. Dr. Juan Klopper's way of describing things was very concise, and easy to understand. It helped me understand a lot of the basic key concepts used in medical research and gave me an insight into how to use it to read research articles along with using the knowledge to conduct my own research. The short quizzes were very helpful in recalling the previously learnt knowledge and testing my understanding of the subject.

I took this course because I heat statistic and I want something easy to understand it, now I have finished the course I would say I did understand a lot of the concepts that will help me in reading and understanding and even criticize some research papers. special thanks to de.juan he really breaks things down to make it looks very easy. now I still heat statistics but I have its basic now ^_^

Very useful course when you have very little background in statistics. You are taught the basic ideas behind the most commonly used statistical tests. The course really gives you a solid base to understand statistics described in scientific medical articles. Actually, after completing this course I felt confident enough to start doing basic statistical analyses on my own research data.

-Would highly recommend for anyone looking to quickly get a basis for evaluating statistics and logistics of medical literature. Notes sections after videos are an excellent supplement to the videos (which are not too long), and does a great job of hitting high points.

-If I could make 1 change I would expand the test section to explain more tests (logistic regression, etc.)

It was pretty good course. The movies parts were done at high level. Very easy to follow and gives a good general view. It would be easier to me to read the statistical part in papers. There are still some small parts, that I believe, could being explain better (I am afraid I still not sure about the central limit theorem :( ) but all in all it was very good.

This is a good intro to bio-statistics course.

It has one of the most intuitive explanations of p-values and alphas.

Some of the explanations, like for sign and rank tests are confusing.

at times I wished there were more problems to do and reading material, but this is perfect for someone who doesn't want a very math heavy introduction to biostats.

It's a good course if you want a general overview of the statistics of clinical research. Personally I was hoping for a little more depth in some of the statistical methods. Some links or suggested readings on the methods would be great as we move along the course. Overall a delightful course. Everything is clearly explained. Thank you Dr. Koppler!