Mar 01, 2017
Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!
Aug 24, 2017
This course by Professor ÇetinkayaRundel is awesome because it is taught in a very clear and vivid way. Lab section and forum are so dope that I love them so much! Definitely strong recommendation!!!
von Chanuwas A
•Nov 21, 2018
The course is very useful and helps me understand the formal testing process of data analysis. I just hope it would cover more of nonparametric testing techniques and dive into a bit more into effect size testing. Anyway, It also provides a lot of insights into important statistical measures of information, which could potentially be extended to the field of predictive modeling and machine learning.
von Diego R G
•May 25, 2019
A very good introduction to the fundamentals of inference and NHST. It's very important that you do all excercises and readings or you will not learn as much. Also, the course won't provide a lot of information on how to use R, but if you spend a good amount of time on your project and make sure that it's good you will learn enough. I had to review a lot of R projects that were not very good, which suggests that some students aren't learning what they should.
If you want to learn statistics or have limited knowledge on the topic, and also want to learn a bit about how to use R, take the course. If you already know statistics and you only want to learn R, then this might not be the course for you, as the emphasis is on statistics per se.
von Henri M
•Feb 14, 2019
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von Duane S
•Mar 08, 2017
This course is an excellent overview of inferential statistic tests / hypothesis tests and confidence intervals. The organization and material is quite good, with exercises and applications using R.
von Jeremy L
•Sep 20, 2018
Solid 3 stars. Lots of material is covered quickly and I learned a lot. The lectures are informative and supplement the book (I definitely recommend reading the (free) book). On the negative side, I noticed that the online discussion forum for the course isn't monitored by the instructors and the mentors seem to respond to only some questions. I noticed that almost all of the questions posted by students in the past year that went unanswered. I mean no one even bothered to respond to them at all. That's shameful, esp. if those students who submitted questions are paying for a certificate.
von Ian R
•Feb 07, 2018
The course did teach statistics but there were some problems with R commands, assignment expectations and grading outcomes. For one, this course really needs to do a better job of emphasizing that the student is expected to use R commands provided by Course 1 (I think it's called "Exploring Data") as well as this one. It would be helpful if students had easy access to all of the labs in that course as well as this one. Secondly, the list of expectations given out for the final project omitted several requirements (apparently we are expected to use R commands learned) though this is a small problem.
The biggest problem is the peergrading. Reviewing other peers was actually very helpful in that it does teach you about your mistakes. For example, I realized after grading others that I had made two major errors and was ready to redo my project if needed or, if I passed, never make those types of errors again. This feeling that you are learning and that this is a quality course is taken away when your grade doesn't match your work. In my case, I got a perfect score which is nonsense. Like I said I made two big mistakes one of which was not including a confidence interval when I should have. What if I made others that I didn't see?
Feedback is important. It is a big part of learning. So is the ability to actually use the skills being taught (the R commands were taught much less clearly than say in Datacamp which this course suggests we use even though it is NOT free and I signed up for the Duke course specifically because it taught statistics using R). It's a good course overall and you will learn statistics; but when you're charging people a fairly high monthly fee, you should deliver on your promises to give feedback and to effectively teach one of the major course goals.
von Aydar A
•Nov 03, 2017
It was good. But I feel like I've spent half of the time untangling sly phrasing of questions.
von Try K
•Mar 23, 2018
While I understand and appreciate that the scope of the class is more focused on the application / ideas of the statistical methods without delving too much into the mathematics, I would appreciate if some of it was used to explain why some equations work the way that they do. For example, in talking about F test statistics, it was difficult to understand the reasoning behind F = variance between groups / variance within groups until I had to look up other explanations elsewhere. While I believe that the instructor teaches well in most parts, I often find it difficult to follow along because she goes through a lot of assumptions and I'm unclear as how / why she is allowed to go on her assumptions.
von Jamison T
•Jul 05, 2018
I should not be charged if I have completed the project and simply waiting for other users to review it. This is dependent on how many users are taking the course at any given time. A bad system that results in users paying more for uncontrollable uncertain factors...
von Daniel H
•Jun 29, 2019
An overview of inference, light on the math, light on the theory, and with an unfortunate failure to reinforce what may be the most important part of practice: what should be done when conditions for a particular method are not met. When you teach students how to evaluate the conditions required for certain methods, but then walk through those methods even when the conditions aren't met, you reinforce poor practice. If you want to use an example where the conditions aren't met, STOP once you find out the conditions aren't met. STOP and REINFORCE the fact that you cannot use a method without meeting conditions. It is not a valuable exercise to walk through the plug and chug calculations anyway. STOP, discuss why you can't proceed, and then move on to another example if you want to give your students an opportunity to practice taking the method through to its conclusion.
von Mrinalini S
•Nov 19, 2018
This is a very well structured and taught course. It is difficult so make sure to dedicate lots of time for videos, practice, and revisions.
von Alain C
•Nov 17, 2018
The best course I have ever done on coursera!
Simpy perfect
von Eyuel M M
•Nov 17, 2018
Just Great!
von Hidetake T
•Dec 03, 2018
nice course. it will definitely gives you skill.
von Gilberto S G
•Dec 19, 2018
Excelente.
von 海鹏 李
•Dec 10, 2018
This cours helps me a lot to understand the mechanism under the numbers and statistic, I really recommend u to follow it if you wanna to be a data scientist!
von Saravanan
•Feb 01, 2019

von Daniel R
•Feb 04, 2019
Amazing course!
von Umair R
•Nov 21, 2018
Excellent teaching style with enough practice to get a good grip on whatever is taught
von Dario B
•Nov 06, 2018
Very interesting material. Statistical inference was one of the great mysteries for me, and it is indeed a technical topic. But the professor does a great job in presenting the material in an intuitive way, giving an awesome introduction. Very interesting real examples too.
Looking forward to have a proofbased equivalent course, though maybe I should focus on a forma probability course first.
von Akshay N
•Nov 14, 2018
Fantastic. As good as it gets. Amazing textbook too
von YASHKUMAR R T
•Jan 16, 2019
I found the treasure.
von Prakhar P
•Jan 22, 2019
The concepts are explained in a very simple and effective manner with the help of a case study. Background knowledge of R will be very handy if one wants to cover the topics at a faster rate.
von Sidhant P
•Jan 25, 2019
This is a great course. One can learn so many things from this course.
von Alfredo J N
•Feb 10, 2019
Amazing!