Sep 01, 2017
Good intro to Bayesian Statistics. Covers the basic concepts. Workload is reasonable and quizzes/exercises are helpful. Could include more exercises and additional backgroung/future reading materials.
Jun 27, 2018
Great course. The content moves at a nice pace and the videos are really good to follow. The Quizzes are also set at a good level. You can't pass this course unless you have understood the material.
Nov 28, 2018
Need more information about linear regression, given material is not enough to understand topic and effectively find solution.
por Anders Amundson•
Nov 26, 2018
Would have liked more problem solving and real-world application examples.
por Susenjit Ghosh•
Nov 23, 2018
Very Useful Course
por Niklas Jahnsson•
Nov 21, 2018
Good and clear course. I was impressed by the quality of the material.
por Denitsa Staicova•
Nov 20, 2018
What I liked in the course is that it focuses on examples and solving actual problems. The quantity and the quality of the lectures is great, but what I really missed is written lectures where one can always lookup forgotten things or read details etc. Also, one thing that I think might be added easily is a reference to Mathematica and Maple's routines. I'm using Maple and it took some efforts to get on track. And finally, I think that 4 quizes per week is really too much for working people. It's true that the tests weren't that difficult, but it took me about an hour to do each, so I think 30 mins of lectures vs. 4 hours of quizzes is a bit unfair. Of course, my background in statistics is non-existent so it may be that it took me longer than average. But I think the course material could have been spread over say 6 weeks for lighter load on the students. All best to the team!
Nov 10, 2018
It was my first Bayesian course. Good introduction! However more accent should be placed on intuitive understanding rather than mathematical formalism. To be fair that the issue not only with this course, that the issue with 90% of all stat courses/books. As for me, I find mathematical formalism is hard to digest, intuitive understanding should come first ... May be it's just because of my limited knowledge of stats. I'll update my belief once I get better understanding of stats:) Thank you very much Dr Lee!
por Robert Tabell•
Nov 07, 2018
Great course for beginners as well as those that need a refresher on the basics!
por Ekaterini Tarasidou•
Oct 31, 2018
I found the need to search for most of the material needed to understand the lessons in other sources. Other than than it was a relatively easy class, which covers nearly the basics. This is not a tutorial on Data Analysis on R, although a short introduction is provided.
por Arnaud Dion•
Oct 30, 2018
Excellent course ! Full of examples and very useful to a deeper understanding of the domain.
por Scott Small•
Oct 28, 2018
This course gives an introduction to the theoretical basics of Bayesian statistics. Before taking this class, I had a very confused view of the whole Frequentist vs Bayesian "debate". I understand now that Bayesian statistics is really about attaching uncertainties to beliefs and producing a clear definition of this uncertainty (especially through the notion of credible intervals).
The course really focusses on theory. I recommend knowing a bit of basic stats concepts before taking the class, such as Bayes' Theorem, basic discrete and continuous distributions, and confidence intervals. If you are not experienced with these, be aware that you will likely need to read-up on them throughout the course. R is used, but the usage is so simple that you should not shy away due to a lack of R experience.
I really have no complaints about the course. After completing it, you should understand the differences between Bayesian and Frequentist approaches. You will also understand a lot of terminology that gets thrown around in data science these days (priors, posteriors, credible intervals).