Back to Introduction to Probability and Data with R

stars

4,736 ratings

•

1,130 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....

AA

Feb 24, 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!)

AM

Feb 7, 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!

Filter by:

By Anil J

•Nov 3, 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 3, 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 4, 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 8, 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 7, 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 Spandan B

•Sep 12, 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

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 17, 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 5, 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 C

•Oct 7, 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 Matias F

•Oct 20, 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!

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 7, 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!

By Samuel O T A

•Dec 9, 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 Nguyen N H

•Feb 16, 2021

This course is great for starters who wish to learn basic concepts about probability. Nonetheless, I recommend you to learn a basic course about R to easily finish the final project on week 5. I truly appreciate the peer review as it helps me see my shortcomings and learn from peers.

By Toan L T

•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 Muhammad I

•Sep 28, 2020

“The course was refreshing, interactive, and interesting. A good mixture of the instructor’s engaging presentations with enough time to do the quizzes and assignments.”

“The course provides useful experiences that will help to improve the overall skills and knowledge in using R.”

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.

- Finding Purpose & Meaning in Life
- Understanding Medical Research
- Japanese for Beginners
- Introduction to Cloud Computing
- Foundations of Mindfulness
- Fundamentals of Finance
- Machine Learning
- Machine Learning Using Sas Viya
- The Science of Well Being
- Covid-19 Contact Tracing
- AI for Everyone
- Financial Markets
- Introduction to Psychology
- Getting Started with AWS
- International Marketing
- C++
- Predictive Analytics & Data Mining
- UCSD Learning How to Learn
- Michigan Programming for Everybody
- JHU R Programming
- Google CBRS CPI Training

- Natural Language Processing (NLP)
- AI for Medicine
- Good with Words: Writing & Editing
- Infections Disease Modeling
- The Pronounciation of American English
- Software Testing Automation
- Deep Learning
- Python for Everybody
- Data Science
- Business Foundations
- Excel Skills for Business
- Data Science with Python
- Finance for Everyone
- Communication Skills for Engineers
- Sales Training
- Career Brand Management
- Wharton Business Analytics
- Penn Positive Psychology
- Washington Machine Learning
- CalArts Graphic Design

- Professional Certificates
- MasterTrack Certificates
- Google IT Support
- IBM Data Science
- Google Cloud Data Engineering
- IBM Applied AI
- Google Cloud Architecture
- IBM Cybersecurity Analyst
- Google IT Automation with Python
- IBM z/OS Mainframe Practitioner
- UCI Applied Project Management
- Instructional Design Certificate
- Construction Engineering and Management Certificate
- Big Data Certificate
- Machine Learning for Analytics Certificate
- Innovation Management & Entrepreneurship Certificate
- Sustainabaility and Development Certificate
- Social Work Certificate
- AI and Machine Learning Certificate
- Spatial Data Analysis and Visualization Certificate

- Computer Science Degrees
- Business Degrees
- Public Health Degrees
- Data Science Degrees
- Bachelor's Degrees
- Bachelor of Computer Science
- MS Electrical Engineering
- Bachelor Completion Degree
- MS Management
- MS Computer Science
- MPH
- Accounting Master's Degree
- MCIT
- MBA Online
- Master of Applied Data Science
- Global MBA
- Master's of Innovation & Entrepreneurship
- MCS Data Science
- Master's in Computer Science
- Master's in Public Health