Back to Introduction to Probability and Data

4.7

stars

3,466 ratings

•

786 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 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 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 Samuel O T A

•Dec 10, 2018

It's a great course, I had acquired new abilities like using R language programming for applied statistics, as well as knowledge about probability and statistics in topics like: sampling, measures of center and spread, data visualization, inference, probability distribution and much more.

By Mariliis J

•Oct 19, 2019

This course was planned very well. It covers topics multiple times but in different forms/approaches, which makes the material easy to learn and obtain. Furthermore, the practical exercises and coding lab were guided enough yet let the learner have independence as well in the solutions.

By Michael O

•Mar 23, 2018

excellent course! Videos were very instructive, book and problems reinforced the course material well. All in all great. Had a little problem getting the knit function to work initially, and it appears as some others did since I saw one project submitted that wasn't knit into html.

By Toan T L

•Nov 25, 2018

Great introduction course on Probability.

The final report is unexpectedly challenging when one has to come up with 3 analysis from a dataset with more than 100 variables.

So if you choose to finish this course, be prepare to spend a lot more time than other normal ones on Coursera.

By Rohit D W

•Jan 30, 2020

It was really a great course, on an initial basis, you will learn different things a lot. And as a statistics student, I enjoyed the coursework, with an r programming language it was different at first but while getting used to it, it's a nice and easy way to deal with data.

By Christopher R

•Jan 19, 2017

I enjoyed the RMD labs. I think they provide a great interactive hands on learning experience that video and paper assignments alone can not cover. The material covered in the labs is worthwhile as well, showing how to dissect that table into different cuts for investigation

By Thomas M

•Sep 03, 2016

Very good introductory course to probability and data. Very hands-on examples and outstanding explanations. I already had several statistics courses before in my life but not in this quality. I can really recommend this course to anyone who to learn more about statistics.

By Karin S

•Oct 05, 2017

Having very little statistical knowledge and no R programming experience before starting the course, I have learned so much! The coursework goes at a good pace, the instructors are very clear and explain things well. I look forward to taking the entire specialization.

By Sanju S

•Aug 12, 2016

Excellent course. Very engaging. The amount of effort the team has put in is very evident. The quizzes in the lecture make you pause, think and reinforce the concepts. I am currently doing John Hopkins data specialization as well, but this is way better. Thank you!

By Raghav A

•Jul 17, 2017

The Course & Slide Material is nice.The examples used help in getting & applying the theory matter taught in the previous videos.It's great.

Only suggested thing is if the instructor could provide a word or handwritten material it would be an icing on the cake.

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