Back to Introduction to Probability and Data with R

4.7

stars

4,219 ratings

•

989 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 Tae K K

•Apr 19, 2016

I have not taken Statistics 101 and Probability Theory 101 since college. This course was a great refresher course for review! I highly recommend this course as a refresher/review course to jump into real-world-application courses down the road.

By Khaled A I

•Dec 12, 2019

The course is very organized and informative. explanation is very clear.

the only issue is that the final project requires R skills that are not taught during the course. The labs during the course is extremely primitive compared to that project

By Charly A

•Nov 26, 2016

The professor is fantastic and the content is top-notch. A great mix of theory and real-world application. The course is not math-heavy but provides enough additional material for one to delve into those details. I highly recommend this course!

By Corina S

•Jun 13, 2020

This course helped me break into the world of R programming pretty easily. I also really enjoyed the course material. The only thing I thought could use some improvement were the instructions for the final project. They were a bit too vague.

By Lindsay C

•Dec 13, 2018

This course was a good introduction to basic probability, experimental design, and data structure. The labs and final assignments made great use of R Studio and markdown. This course is best suited for someone who is proficient in R already.

By Prashant S

•Aug 22, 2017

The course was structured and explained in easy to understand fashion. The project submission at the end of the week was a challenge for a beginner like me, but having submitted it and gained a good grade on that is a satisfying experience.

By Yu L

•Apr 17, 2018

Useful course! very clear to make points. The instructor is very good at teaching. recommend. One thing I don't like is that for the peer review project, you have wait to long before some one else review your work and get the certificate.

By Muhammad F

•Mar 30, 2020

The course give me a basic understanding of basic statistics and show me how to employ statistical calculation and visualization by using R studio. One of the most exciting things is the project assignment which analyzes real-world data.

By François P

•Jul 26, 2016

A very nice intro to the topic!

The course is problem-oriented and introduces important concepts in relation to questions that will interest the student. It also gradually introduces R and its use for statistics analysis. I recommend it.

By Saransh A

•Jun 27, 2016

Absolutely wonderful course

With the basics of Probability and Statistics to it's implementation in R

Everything is very simple and the text book is very much in accordance to the course, also the lab exercises are very well planned out

By James H

•May 05, 2016

Interesting and enjoyable. Very clear explanation of concepts in the videos and text. Begin using R in the first week, with exercises that allow you to pick up a few commands fairly easily and start analysing data and creating graphs.

By Ignacio S U

•May 28, 2017

I've been using coursera for over 4 years and never had I seen a course as good as this. It is pretty concise and integral. It plays between theory and practice and recommends a handful of references. The course is totally worth it.

By Wang Y

•Oct 18, 2016

A great course to start learning about probability and statistics, as well as basic R programming. The final assignment is quite challenging for an introduction course, so plan ahead to make sure you have enough time to complete it.

By Guerville J

•Mar 20, 2020

Great explanations - it was good to review all the foundations and learn R in the process.

The final assignment was very long to achieve.... more 8 hours than the 2 hours advertised.

But I really learned how to use R in the process.

By Bharath S

•Aug 10, 2020

This course helps students pursuing academics in statistics by laying a strong foundation in the field of statistics and probability.

The course has been formulated with excellent examples to explain concepts in an effective way

By Alberto P

•Jun 22, 2018

Great introduction to probability. It's brief, it contains great tools and strategies on how to evaluate a statistical situation. It shows a nice start on how to use R with RStudio. Great for beginners on R and/or probability.

By Minas-Marios V

•Oct 28, 2016

Very good introductory course! The lectures were very interesting, highly due to the instructor's engaging and passionate attitude ! Very smart and helpful quizes too, with a very detailed data analysis project at the end!

By Balachandar K

•Jun 27, 2016

Professor Rundel makes the subject interesting by quoting real time examples in the videos. This course will certainly help beginners in statistics. The entire specialization is a step by step process to master statistics.

By Liang Y

•Mar 16, 2019

I have learned a lot details which I am confused from other courses in the course. I think that it can take more details in it, such as the inference about the formula of the binomial distribution!

Thank you a lot teacher!

By anthony w

•Sep 22, 2017

Im really glad I took this course and had the direction of a competent teacher and staff. I made more traction than studying on my own. Its amazing how flexible R is and I look forward to using it professionally one day.

By shankha m

•Jan 16, 2019

The best learning happened through the peer graded project and reviewing others' work. However, the course focuses more on statistics. If the learner wants a good grounding on R this may not be the best course to take.

By Jie W

•Mar 20, 2018

Absolutely a must taken course for social science students. The instructor is very articulate and explains theories， concepts and formula clearly. The exams and assignments are necessary for strengthening your learning.

By Aakash K

•May 25, 2020

The course clearly builds the bases of Statistics from very scratch. The best part is the implementation via R Labs and final project. Highly recommended and looking forward for the next course of the specialization.

By Derrick G

•Aug 13, 2019

This is great. I have so many notes from only the first Week of classes. The teaching style is very engaging for an introduction class. A little theory, a practical example or two, and then a practice project. Great!

By Hamza A D

•Mar 16, 2020

The course was amazing! Especially for me as a beginner, it was not much difficult to get the hang of things!! Hats off to the amazing teacher and her enthusiasm to teach difficult things easily. Highly recommended!

- 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