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Learner Reviews & Feedback for Introduction to Probability and Data by Duke University

4.7
stars
3,776 ratings
869 reviews

About the Course

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....

Top reviews

AA

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.

HD

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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626 - 650 of 851 Reviews for Introduction to Probability and Data

By Raj K P

Sep 17, 2017

Liked it

By 张扬

Aug 13, 2018

helpful

By Durgadas K

Dec 17, 2018

thanks

By Ale D

Jul 07, 2017

Great!

By 童瑶

Jun 27, 2017

useful

By Mohamed A

Jan 12, 2017

Thanks

By Nimish B

Sep 19, 2019

Great

By Shiva P L

Jul 16, 2019

great

By Candice

Dec 16, 2018

Good!

By Christopher O

Aug 08, 2016

Great

By umershahid

May 20, 2020

good

By 林昌璟

May 07, 2020

Good

By Khawaja M O

Dec 23, 2019

BEST

By MAYANK N

Nov 08, 2019

good

By Dhruv C

Nov 08, 2019

good

By Finn张策

Dec 28, 2017

nice

By 林轩平

Nov 22, 2017

good

By Joseph

Nov 28, 2016

Good

By 李纪玺

Oct 01, 2016

非常好!

By Divyesh S

May 25, 2020

na

By 张石磊

Nov 20, 2017

G

By Tobias M

Mar 21, 2019

This is a really great course, but it is NOT easy!

There is a steep learning curve for people who are beginners in R with the project at the end being quite challenging. The stats part of this course starts with a good learning curve and picks up speed quickly as well. The videos available for this course are generally good quality but could be ironed out a bit more in terms of some rough editing. You can see the age of the video material showing up in some of the videos.

Overall there is good help available on the discussion forums and using the statistics textbook and practicing with the example questions is highly recommended.

The time required as stated for each and every aspect of this course is vastly underestimated, a trained person will be able to finish this in the given time but a beginner can easily double or triple the time needed for the tasks.

Weekly time usage for class and all example questions plus digging for problem solutions in the forums is between 7 and 10 hours, the project at the end for an absolute beginner alone is easily another 10 hours hacking in R plus some extra time getting used to the project material.

Do NOT attempt this course if you can not dedicate enough time for this course!

By Jaclyn J

Sep 19, 2019

The lectures in this course were fantastic. The professor clearly explained complex topics, and I would gladly take more courses from her. However, I can't help but think that I wouldn't have been able to complete the final project successfully had I not taken previous classes in R. I don't think there was good alignment between the course itself and the final project. Also, the final project involved complex survey design data, but it was not clear if we were suppose to account for this (I assumed not because it seemed out of the scope of the course). I asked this question to the discussion board but never received a response. It was less satisfying to complete an exploratory data analysis knowing that all my numbers were inaccurate because of not taking weights into account. I would suggest a different dataset for the final project.

By Mark D

Dec 19, 2017

I have been looking for this type of course for years that combine a solid statistics background and learning a new piece of technology. Most statistics class are cram classes where the student needs to choke down a formula, regurgitate it for an exam, hope it is correct, quickly for get it and move onto the next. This class is the opposite. Concepts are easy to understand, logically thought out and in bit sized-pieces.

Professor Çetinkaya-Rundel is the best statistics instructor I have ever had. She clearly explains concepts, backs them up with applied examples and the textbook is extremely well written. I enjoyed learning R but sometimes the statistics lesson and the R were divorced from each other. The final exam was an excellent concept but it was a little daunting and way above my pay-grade.

By Emmanouil K

Apr 03, 2017

Overall, I would recommend this class. I found that the preparation towards the final project could use some improvement, especially plotting using the 'ggplot2' package. Why not work on this during Week 4 through an assignment that works on this? This would have made it easier to focus on the research questions of the project and less on the graph making mechanics. Also, I found that the project was a little bit too open-ended and could have used some more input from the instructors' side. The material during the four weeks of the course was really good and thorough but perhaps a little too difficult to follow for people who have absolutely no background in probability theory. Maybe one should audit the course first and then decide whether it would be a good idea to formally enroll.