more time needed to reiew R

good, but hard sometimes

The formulae did not work on my laptop and could not solve this problem and could not contact the instructors. The instructor way of illustration is simple and nice so I would prefer more videos than the too much readings in the last week .

I felt this course gave a good introduction to using R for statistical testing and benefited from doing so using health data. My main aim was to learn R but I felt a course that just concentrated on the programming aspects would not suit me. I think this course is good for those new to R who might not have experience in other programming languages. The videos and the lectures were well put together and the quizzes seemed well designed to pick up misconceptions or common mistakes. I would recommend this course

Until 2016, I was building Financial and Accounting Models for MBA Programmes. That I was teaching as an MBA Dissertations Supervisor, and Senior University Business School Lecturer (Professor). I am now working Part Time for the NHS, and I am aiming to specialise as a Senior Data Scientist with the NHS. This is Specialisation, is one of several first class steps that one can take towards such an aim.

I was so apprehensive about starting this course because I associated R with programming (that I very much dislike) but it has been very fascinating and I've learned so many useful things like creating histograms and doing hypothesis testing in R! It's certainly not as scary/difficult as I thought, and I'm looking foward to the next few courses!

This course is well designed for beginners. Everyone who wanted to learn the basics of sampling, statistical analysis (mean, mode, proportion, p-value, degree of freedom and many more) must take this course. Especially if anyone wanted to learn R and do not have a background of statistics then this is the best course.

This was an excellent course! I have a MPH degree and I took this course as a refresher on statistical concepts but also to begin learning R. The professor was great and the examples really started to reinforce concepts within R. Overall, I found this course to be very informative and useful for my day to day work.

Good session, clear content, good flow, excellent assignments and practice sessions

Only in one place, tables of assignment for chi square test, total mistake was there. In one quiz, mean value of 11 and 14 samples were not accepted as correct. The reason behind this is not explained. As a whole, excellent course.

This is a very well explained course which explains with short videos, readings, stories very important and somewhat basic aspects of statistics in public health field. I definitely recommend this one even if you already have knowledge, as it forces you to deepen the critical thinking as (future) statistician.

I wasn't confident of myself in using R. It always seemed to me that IT professional are better equipped to learn it. By confidence has increased to a great extent and I am happy to say that I will be completing this specialization by Imperial College London.

Thanks Coursera and Imperial College Team :)

If you want to really understand statistics for data analysis, this course is a great idea. The professor, Dr. Bottle actually did a great job on the contents of this course. I had a statistical background, and this course helps me to understand some concepts that I didn't understand before.

This introductory statistics course is far better than the similar one I took with Johns Hopkins University because there are fewer recorded lectures and more work involving reading. it is also broken down into smaller "chunks" and Alex Bottle is very engaging in his lectures.

Excellent course! I must say that I have genuinely learned a lot about medical research using statistical tools from this course. And there were many concepts of statistics that that weren't clear to me. This course helped me understand those concepts as well.

This is the best statistics course I have ever taken (and I have taken many!). The professor clearly explains all the concepts reviewed in this course and the exercises are designed in such a way to make it easy to understand the nuances of the theory.

Great introduction to R and statistics related to public health research. I recommend doing the readings and practice problem as well. I was a bit confused in the beginning but I supplement this lesson with other introduction to R classes online

Really good course covering statistics. I've covered this topic before in other courses, and I was impressed at how the instruction and quizzes cover the material in a clear and nuanced way. This course is introductory but not basic.

a brilliant introductory course to concepts in statistics as well as using R for statistical analysis. thoroughly enjoyed the engaging nature of the facilitator and numerous practice exercises, real-life examples and readings

Perfeita introdução para uma área de estudos tão importante e relevante na atualidade, quero continuar minha formação nessa área, pois este curso me mostrou que estou no caminho certo! Obrigado professor Alex Bottle!

Great start to statistics after so long. I can't wait to learn more from the other courses on the specialization. It was fun, interesting, practical, thoughtful. Not easy but it is worthy.

The instructor videos are amazing- very relatable, applicable, and comprehensible! The principles are simplified as best as possible. This courses also good if you are very new to R.

Excellent course with really good teaching. Felt like it developed a good grounding in the basic topics. Would recommend having a little R experience prior to taking this course.

Excellent introductory course on statistics and its facts. It helps to assess several testings based on different data types and interpreting values using R programming.

I liked the way the whole course has been designed. I never felt stressed up. It was all fun. The speaker was excellent in blending real life example with statistics.

Great introduction towards statistics in public health, with nice addition of R programming language. The material is meticulously explained and easy to understand.