Instructor is excellent. While I bought the recommended book I hardly referred to it. The response from the mentors (especially David Hood) in the discussion forum to every question has been very prompt and precise. Overall the combination of the Instructor, the illustrations in the videos, the practice tests and the online support of the mentors makes it an ideal online course. I was able to finish this despite being in a fairly demanding full time

Al enfrentarme al proyecto final me di cuenta que quería hacer muchas cosas y no contaba con las herramientas, tal vez porque lo que quería realizar se encontraba en un nivel más avanzado así que accedí a buscar más info en internet. Descubrí que podemos buscar más ayuda por fuera del curso y que no debe ser una limitación, aunque me tomó días completar mi proyecto traté de hacerlo lo mejor posible. Muchas gracias por lo aprendido en este curso!

The course was very good! The instructor explained the concepts very clearly. She also took effort to differentiate between commonly confused concepts. The final project in R was tough, but through it I really used my own knowledge to approach a question like an actual research project. I also learned to search for R commands that were not taught in the course with the help of the RStudio cheatsheets and online platforms like Stack Exchange.

Excellent introduction to R and probability. The lectures were very clear and well structured.

I particularly enjoyed the final project, and the fact that we were given free reign over the research topics: what questions to ask, and also how to structure the answers. It is an great opportunity to further the knowledge acquired during the lectures and become familiar with R capabilities. The feedback from the other students was very valuable.

It is the best course I have taken till now on Coursera. Having a python background, my only concern was that I would have to learn R for this course and I am sure there are others in the same boat. My advice to them - Take this course anyway. You will build a strong grasp on probability, and also end up learning R (Understanding its basics barely takes time since the syntax is just as easy as Python) and open up a myriad of opportunities!

Mine Cetinkeya-Rundel' explains the concepts in a very very clear manner.

I actually started with other statistics course on Coursera. But found it going too fast. A lot of ideas were poorly presented. I was quite frustrated with one topic, so I searched online for detail elaboration and found Mine Cetinkeya-Rundel's youtube videos. Her deliberate explanation built my confidence. Hence now I'm at her class and I really enjoy it overall.

This course is really helpful to have a better understanding of fundamentals of probability and data statistics. The course mainly focuses on basic concepts of probability and how to apply them. The assignment provided was very helpful and challenging. The peer graded project allows me to evaluate my fellow course mates which really boost my confidence as make me feel like an invigilator and provide the basis for my academic career.

This is a very good course to learn (or review) the foundations of statistics and how R can be a great companion tool to augment a solid understanding of the topic.

The instructor speaks clearly and at a fast enough pace that there is no time to pay attention to anything else. I appreciated the lectures, slides and there is a free PDF book which is also well written! I am looking forward to the other courses in this series!

The course was really beneficial to someone with no R experience. Having taking statistics courses before I was mainly interested in the use of R for computational uses of statistics and analysis. The course provided those means and more. I'd recommend using RStudio on your own computer versus the Data Camp tutorials however as when it comes to the project at the end, you'll be extra comfortable with the use of RStudio.

Very well-designed course with interesting topics. The supplementary reading proved essential for me. The recommended times are not very reliable. The only down side is the extent to which R is used (not enough in my opinion) and I did not feel well prepared for the final assignment but this may be due to the type of research questions I set myself. Overall, very interesting and I am glad to have done this course.

It's a great course for who want to learn applied statistics using R. The main topics are deeply explained. Exercises and other materials, like the OpenIntro book, are challenging. And final project gives you and idea of your new skills levels. The only attention point, for me, was the unbalance between the expected time to do the final project and the real demand. But it was a very, very rich experience for me.

Introduction to Probability and Data with R was the best course I have taken so far via Coursera. The course materials (textbook and RMD files for R) were very helpful and well organised and the examples given in the videos were elucidative. I will certainly continue the specialisation tract. I highly recommend it to everyone interested in using computational methods to understand data. Teşekkürler Mine Hocam :)

The course provides a solid introduction to probability and statistics and the instructor clearly explains all the topics. The quizzes and labs were very useful in reinforcing the concepts that were covered in the course. I was a little disappointed that R is used instead of Python but after using R Studio, which is a very nice tool, I can appreciate that R may make the course more accessible.

Wonderful course. Provides direction but after that is pretty much self-driven with little spoon feeding, which is how courses should be. If you're looking to learn R this may not be the best place to start since this course doesn't talk much about base R and goes straight to tidyverse packages.

I think links to more mathematical proofs for some concepts would be useful for advanced learners.

Everything is clear and well organized. But, the final assignment might be little bit difficult for a beginner. The estimated time for that is 2 hours but I think it would take more than 2 hours for a beginner (A day or a two). It would be great if there are more explanations and guidance for the last assignment. But, anyone would be able to complete if he/she has enough time to spare.

I really liked this course, it is very well organised and the explanations are good and sufficient. However, this is not a course for someone who haven't work with R before. You need to have at least some basics of R to complete the labs and the final assignment. It was not easy to complete the final assignment but absolutely worth the effort. I learned a lot during this course.

My name is Jose Antonio from Brazil. I am looking for a new Data Scientist career (https://www.linkedin.com/in/joseantonio11)

I did this course to get new knowledge about Statistics in DataScience and better understand the technology and your practical applications.

The course was excellent and the classes well taught by teachers.

Congratulations to Coursera team and Instructors.

I've taken several introductory statistics courses and this one is by far the best. Material is covered quickly and clearly, and there are extra explanations for the questions that other courses left me puzzling over. A really well taught course, highly recommended. The only minor drawback of this course is that the sound quality could be better, but that's a minor point.

A well-thought course on statistics. Some topic were explained too fast on the video, but I was able to catch up on the things that I have missed reading the text book. By the way, the text book is really well written - easy to read, concise and comprehensive. Great course overall. I wish they gave more additional info on R programming basics, but that's the only concern.

The course was taught in a very illustrative manner with enough repititions over the concepts! A very deep dive from absolute basics to how's and why's. The assignments related to coding can come with some clearer explanations and the project is a little beyond the scope of the coding taught, however it will be an intensive and incredibly helpful venture if completed.

A nice blend of statistics, applied labs using R, and a final exploratory data analysis project that the course prepares you for very well. The instructor is informative, easy to understand, and brings enjoyment to the video lectures. The open textbook is well aligned and easy to read. The quizzes and labs are challenging. The mentors are responsive and helpful.

Very useful, especially in R. I really like the final project since it really gave me the opportunity to explore the dataset on myself. it was a little bit challenging for me since I had to integrate all of knowledge I learned here. But I have to say it is really useful. The narrator is brilliant too. Each concept and statistic method is clear and acceptable.

This course did an excellent job of challenging at an appropriate level. Full disclosure, I have never done any programming in R and have been playing catch-up on that part the whole time but the materials are set up in a very helpful but not too hand-holding way. I particularly enjoyed the final assignment. It really served to drive home the material covered!

Excellent guidance, videos and a free ebook to guide you through the process. I managed to learn alot and do well on the final project finishing the course with 95% even though I had 0 programming experience. If you are willing to spend the time studying, and reviewing the very helpful material, there is no reason whatsoever you will not be able to do well.

This course was very well taught. The concepts are interesting and the presentation is well-organized. The examples and projects are very helpful in helping us practice what we were taught. The final project is challenging, and is indeed a stretch assignment. However, all the concepts and coding taught in the lectures should prepare us for the challenge.