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4.7

stars

3,789 ratings

•

874 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.

Sep 04, 2019

Very clearly explained and the pace is awesome! I really enjoy each deadline and l can already see how it is impacting my day to day work and life. I ook forward to completing the course! Thank you.

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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 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.

By Leon M R

•Jan 14, 2020

Through this course I finally got to understand R as a whole. It was also possible to begin to understand how language works. The course is quite didactic, but requires some familiarity with basic statistical concepts and data visualization, which I noticed especially from the projects I evaluated.

By Carlos M

•Aug 11, 2016

Great course! This has been one of the best courses that I have taken at Coursera. I really liked the fact that we have a free book for the class and there are optional exercises for practicing what we have learned at the end of each week. The instructor knows the subject and is very clear.

By Gouri D

•Jun 19, 2018

Prof Mine Cetinkaya-Rundel's explanation, narration and examples are simply superb! I decided to subscribe for this specialization after trying it for the free 7 day period, and it is totally worth it. I will look for more courses by this team. Thank you all. The course content is very good.

By Duane S

•Jan 29, 2017

This course is a great introduction to learning about statistical thinking in R. The emphasis is of course on probability and data (especially distributions and exploratory analysis), but there is also a very nice integration of R code and introductory coding to complement the main material.

By Sandro H

•Mar 07, 2020

A cornerstone for anyone to dive into the complex world of statistics. Dr. Mine is not only in perfect command of her material, she also made it fun to learn enough for me to have stuck around until the end of this course. I am confident of tackling a new challenge: inferential statistics!

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