Back to Introduction to Probability and Data with R

4.7

stars

4,033 ratings

•

939 reviews

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The concepts and techniques in this course will serve as building blocks for the inference and modeling courses in the Specialization....

Jan 24, 2018

This course literally taught me a lot, the concepts were beautifully explained but the way it was delivered and overall exercises and the difficulty of problems made it more challenging and enjoying.

Mar 31, 2018

The tutor makes it really simple. The given examples really helped to understand the concepts and apply it to a wide range of problems. Thank you for this. Wish I could complete the assignments too.

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By Chin J L

•Feb 08, 2018

This course gives a nice introduction to fundamental concepts of Probability and Data. It also gives a glimpse on scientific studies. The topics are very well presented and the study material is excellent.

I highly recommend this course to anyone who does not have a background on the subject and wishes to have a better understanding of Statistics

By Yize H

•Oct 04, 2016

This is a great course, very helpful for people who are interested in statistics and R. I learned a lot from the lecture. Apart from the compact lecture, I also learned a lot from the peer review process, the work I reviewed and feedback I got were very helpful, I was also shocked by the efforts present in the work and feedback. Great community.

By Ben G

•Aug 29, 2016

Excellent introduction to Statistics and Probability. The course progresses at a nice pace - not too much too fast. The textbook is a great resource, and it's written in a very easy to digest way, making the concepts clear and approachable. The videos further reinforce the textbook and help clarify the material.

This class is highly recommended.

By Puneet K

•Jun 01, 2017

I doubt there are many professors around the globe who can match Mine Çetinkaya-Rundel's clarity of thought, her structured thinking and most importantly the the way info was packed into this course. Love the Openintro book, I still refer to it in my day to day work. Great going folks from Duke. Will see you in the Inferential Stats Module !

By RAGAVAN N

•Jun 14, 2016

It took less than 3 days overall for me to finish this course, but I did this just because I wanted to refresh the basics and see if I am missing something. At the end I learnt quite an amount. Prof. Rundel's explanation is clear and concise. I would take all the courses in this specialization just because of the way she explains things.

By Stella L X T

•Jun 06, 2020

The learning curve is steep - the difference between the lab exercises in the first four weeks and the project to be completed in the last week is huge. But I think it teaches a critical component of programming, which is to develop a self-reliant attitude and learn how to seek answers on the web. Great course, looking forward to more.

By Amruta G

•Apr 07, 2019

The course has been handled really well! I learnt a lot. I took this course to revisit the basics and get them conceptually clarified. And I am completely satisfied with what I have achieved.

The R programming part need instructions on how to work with an R Markdown File, I feel, as I myself spent too much time trying to figure it out.

By Robert S

•Dec 06, 2017

Great, diversed material presented in a lively fashion. Inspiring and well explained. The supplementary coursebook with exercises gives the opportunity to study the subject deeper. A lot of real-life examples and a convenient way to practice using R. If the Statistics is for you, this will increase your motivation to study it.

By James G

•May 23, 2016

Course covers a lot of material very efficiently. Instruction is concise, and provides a free online textbook for deeper learning on topics in case you don't fully understand them from the lecture. Be aware that the final project is a serious chunk of work, maybe 1/3 to 1/2 of the total time it took me to complete this course!

By Clinton B

•Apr 29, 2018

Excellent introduction to Statistics, Probability, and Data Visualization! The professor explains it extremely well and supports her instruction with helpful examples. The associated textbook is both free and high quality. The instructor of the course was a co-author of the textbook which ties the course together very nicely.

By Serapion P

•Dec 06, 2016

All the concepts are very clearly presented and the instructor is really a great teacher!

What I liked the most is that special attention is given to the fine distinction between statistical concepts that students easily confuse, myself included.

The mentors are also very helpful and very prompt to respond to any questions.

By Shao Y ( H

•Feb 07, 2017

I love how concise the lectures are, and also the quizzes provide explanations to questions I've done wrong. That's very helpful indeed. This is my first Coursera course with peer-review assignments - I'm impressed that classmates give useful and encouraging feedbacks. I also learnt a lot from reading other people's work.

By Chanuwas A

•Nov 21, 2018

The course is rather easy to understand and covers most fundamental knowledge of probability that we need to know for data analysis purposes. However, the coding exercises are not enough to provide us an extensive technical skills for performing exploratory data analysis. But overall, it's a fun and awesome course! :)

By Md H U

•Jun 20, 2018

Wish I had given statistics its due in my undergrads, either way if you were wise (unlike me ;)) or otherwise, this is the course for you if you want to brush up Statistics or want to pursue it from Zero. The Final submission for this course would give you a handsome understanding of both - Statistics as well as R.

By Anil J

•Nov 03, 2016

Very informative and helped clear up the basic concepts from Probability, Sampling and the inference. Very lucid and easy to understand instructions. Introduction to R Studio was a little daunting for me, as I am unfamiliar, but hugely satisfying to grasp the basics and what all it can do for Statistical inference.

By Jeffrey G

•Sep 03, 2018

This course reflects a new and better way to start approaching probability and data, using modern tools, texts, and approaches. It is a genuinely 21st century approach. The presentations, the labs, and the free textbook, are all in sync together to help people get the concepts and gain real comfort with the tools.

By Kevin L

•Jun 05, 2017

Lectures were very well-prepared, slides were engaging, and there was a lot of optional but helpful reading material and exercise problems given. Overall a very well delivered introduction.

The final project was challenging in that it was open-ended, but it was also an opportunity to practice independent learning.

By Paul N

•Aug 08, 2016

A great course for a practical introduction to R and to statistical concepts. Sets a great foundation for more advanced courses as part of this series or others. The tutor explains things really well and the examples bring theory into action clearly. The R labs really do help to solidify learning. Recommended.

By Wilfred M S

•Sep 07, 2018

This is an excellent course with well articulated methods of teaching, visual presentation with well prepared learning practices. Learning is flexible provided the learners provide time in the course of the week however busy. It is simple to follow and enough support provided at any time online for the learner.

By Harsh J

•Mar 13, 2018

Very well structured if you wish to understand the basics of statistics along with the basic usage of the functions in R. Could cover more basic aspects of using R independently and methods to load data from third-party sources so as to enable independent usage of the software post completion of the course.

By Natalia V C M

•Oct 18, 2019

The course is really good, thank you so much for your work. I just would like that there would be available corrections for the bad answers in the quizzes, to know what we did wrong and learn, also I would like to receive an evaluation of someone of the teachers in the final lab, not only of my classmates.

By Akash R

•Dec 26, 2018

It was a highly interesting course in which we learnt topics at an easy and understandable pace. The understanding of the project was consolidated further using examples. Lastly, the peer reviewed project had us apply all our understanding on real world data set which is greatly important in the long run.

By Jennifer K

•Jul 05, 2017

The professor is so engaging and explains everything in a very clear and organized way. The project at the end of each week is a real challenge and requires you to understand well what you learned. There are additional finger-exercises in R on datacamp.com in connection with this course, which is great.

By Adolfo O

•Oct 07, 2016

I enjoyed this course! Extract information of a data frame, observe this information with R, the bayes rule and how obtain the quantiles are some skills that I learned in this course. I recommend it amply, and in my opinion the examples characterized the topics very well and in a form very interesting.

By Antonio M

•Apr 25, 2020

Great introduction to Probability and Data. The course also explains some fundamentals of Bayesian statistics.

Every concepts was explained very effectively and lots of exercises (with and without R) were provided. I would warmly suggest this course to anyone interested in an introduction to Statistics.

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