Retour à Introduction to Probability and Data with R

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4,941 évaluations

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1,189 avis

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....

AM

7 févr. 2021

After trying several courses to get me started with R programming, this one came to the rescue and had all the info I wanted. It also provides a great way to practice through labs and a final project!

AA

24 févr. 2021

I always wanted to learn statistics from scratch, but I never had a good university teacher. Here I found a good teacher and also the opportunity to learn whenever I want ( and skipping parts I knew!)

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par Serapion P

•5 déc. 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.

par Shao Y ( H

•7 févr. 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.

par Chanuwas A

•21 nov. 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! :)

par Md H U

•20 juin 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.

par Anil J

•3 nov. 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.

par Jeffrey G

•3 sept. 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.

par Kevin L

•4 juin 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.

par Paul N

•8 août 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.

par Wilfred M S

•7 sept. 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.

par Spandan B

•12 sept. 2020

A brilliant course which has introduced me to the concepts of probability,data and Statistics in general in a lucid and clear manner.The exposure to R Programming through RStudio has certainly helped me and it will be useful as I intend to do research in Economics for which knowledge of R is very much required

par Harsh J

•13 mars 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.

par Natalia V C M

•17 oct. 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.

par Akash R

•26 déc. 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.

par Jennifer K

•5 juil. 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.

par Adolfo C

•7 oct. 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.

par Antonio M

•25 avr. 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.

par Leon M R

•24 juil. 2021

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.

par Matias F

•20 oct. 2020

Challenging course. I guess the best of the course is the teacher.She explained complicated concept in easy way.She relaited every concept with problems of the real life. I hade some problems with the practices in R because i wasn´t familiared with that programm. I hope improve for the other cours!

par Carlos M

•11 août 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.

par Gouri D

•19 juin 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.

par Duane S

•29 janv. 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.

par Sandro H

•7 mars 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!

par Samuel O T A

•9 déc. 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.

par Mariliis J

•19 oct. 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.

par Michael O

•23 mars 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.

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