Back to Introduction to Probability and Data with R

4.7

stars

4,035 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.

Filter by:

By Erin A

•Oct 18, 2019

This course made principles of probability interesting, going beyond the usual examples of coin flips, dice rolls, and card draws. The discussion about the limits of which observed trends can be applied to a greater population of interest was clear and the project gave us an opportunity to put it into practice ourselves. I especially liked the opportunity to ask questions of a large dataset and generate tables of data and graphs to illustrate these tables a bit more clearly. I feel I now have a good foundation upon which to build!

By Monique O V

•Feb 19, 2020

I highly recommend this instructor and this course! Excellent teaching, good practical examples that show you why statistics are such a useful technique, very clear lectures, good step-by-step explanations of solving example problems. The free textbook (written by the instructor) that accompanies the course is likewise excellent. If you watch the lectures, read the book, do the problem exercises at the end of each section of the book, you will pick up an excellent grounding in statistics.

By Lenka B

•Apr 24, 2020

I enjoyed the course very much. I appreciated that the course was teaching practical skills that we could immediately apply to solve problems using real data. I was pleasantly surprised that I was able to explore a big dataset from a US survey, formulate my own questions and actually get some answers! Although I found some of the assignments challenging, and I spent on them more time than expected, it was worth it. I guess it helps to know some basics of R programming beforehand.

By Richard N B A

•Apr 13, 2016

Interesting, information-dense and well presented lectures by someone who obviously has a deep understanding of the topics and who is passionate about teaching the subject. Added to that: a great course textbook and useful R tutorials with a focus on commonly used libraries such as dplyr and ggplot. Beginner and intermediate statistics students, as well as teachers interested in the presentation of statistics theory and practice, can't go wrong with this course.

By Sujoy S

•Oct 18, 2017

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

By roxana t

•Feb 10, 2020

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.

By Cecilia L

•Jun 26, 2019

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.

By HEMANT S G

•Apr 06, 2018

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.

By Noah

•Oct 01, 2017

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!

By Kimberly G

•Sep 06, 2017

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.

By Bruno P d O

•May 29, 2019

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.

By Mabeesha P W

•Jun 14, 2020

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.

By Sandra J G M

•Jun 30, 2020

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.

By Jose A R N

•Oct 22, 2016

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.

By Karen J

•Aug 22, 2017

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.

By Nikolai K

•Jun 02, 2017

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.

By Gunjari B

•Nov 29, 2018

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.

By Damon R

•Oct 08, 2016

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.

By Chuwen Z

•Nov 24, 2019

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.

By Christopher W C

•Jun 29, 2020

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!

By Nicolas M

•Jun 18, 2019

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.

By Jose M P C

•Jul 12, 2020

It has been a very interesting course for me, I have expanded my knowledge of probability and descriptive and inferential statistics, I have learned to use R to perform these calculations, and finally, I learned the incredible possibilities of making professional and useful documents with RMarkdown. Thank you very much to all the teachers of the course!

By Omar M

•Apr 20, 2020

If you need a statistics refresher or an introductory class to probability, this course is definitely the best one you will find, don't think it twice, just sign up. Professor Mine Çetinkaya-Rundel is hands down one of the best teachers I've seen, she does a great job at explaining complex concepts without diluting the important theoretical information.

By Adán

•Apr 09, 2020

El curso es excelente, la profesora lo imparte muy bien, de forma concisa, clara y fácil de entender. Además, el aprendizaje de R es también sencillo y muy muy útil. Igual que el proyecto final.

Si tuviera que poner una pega, sería que es una pena que sea tan básico. Hubiera estado genial que durara una cuantas horas más. ¡Muy contento de haberlo hecho!

By Krishnendu S

•Apr 15, 2019

Excellent! mind-blowing! I am immensely impressed by the way the coursed is designed. Very well balanced introductory course with an wonderful introduction of R (which is very needed for modern day statistical problem with huge data)! So extremely recommended for those who wants to kink start their understanding with statistics (in any field!!)!

- AI for Everyone
- Introduction to TensorFlow
- Neural Networks and Deep Learning
- Algorithms, Part 1
- Algorithms, Part 2
- Machine Learning
- Machine Learning with Python
- Machine Learning Using Sas Viya
- R Programming
- Intro to Programming with Matlab
- Data Analysis with Python
- AWS Fundamentals: Going Cloud Native
- Google Cloud Platform Fundamentals
- Site Reliability Engineering
- Speak English Professionally
- The Science of Well Being
- Learning How to Learn
- Financial Markets
- Hypothesis Testing in Public Health
- Foundations of Everyday Leadership

- Deep Learning
- Python for Everybody
- Data Science
- Applied Data Science with Python
- Business Foundations
- Architecting with Google Cloud Platform
- Data Engineering on Google Cloud Platform
- Excel to MySQL
- Advanced Machine Learning
- Mathematics for Machine Learning
- Self-Driving Cars
- Blockchain Revolution for the Enterprise
- Business Analytics
- Excel Skills for Business
- Digital Marketing
- Statistical Analysis with R for Public Health
- Fundamentals of Immunology
- Anatomy
- Managing Innovation and Design Thinking
- Foundations of Positive Psychology