学生对 加州大学圣克鲁兹分校 提供的 Bayesian Statistics: From Concept to Data Analysis 的评价和反馈

Prof Lee derived the formulas in an upbeat way, which helped me learn. I'd suggest putting the actual lectures into pdf for later reference, like is done for supplementary material. Homework assignments were challenging and educational. You might suggest a review of prob distributions as pre-requisite.

Fantastic first course. The only concern I have is with the software choices. I have neither R nor Excel, but was able to easily use google Sheets. It might be worth mentioning to students that this is an option. There is even a stats package that claims parity with one of the listed packages for excel.

The quizzes in the course are very well elaborated and designed to help you learn points and details not explicitly stated in the lectures. The contents and pacing are just about right for me. Perhaps the section on normal inference would need more elaborated as this part was the most difficult for me.

This course provide the theoretical basics for anyone who wants to understand, and hopefully work with, Bayesian stats. Prof. Lee's exposition of the math behind Bayesian stat is precise concise and to the point. If I, with only high school math from age ago, could understand, I believe anyone can.

Very nice course that in my opinion nicely fits between Bolstad and Gelman in difficulty (talking in popular Bayesian Data Analysis books). Herbert Lee does a very good job at building one's intuition and understanding in the general Bayesian inference. Good starting point for moving on with Bayes.

Amazing. Simple, fast, dense, very well taught. I loved the professor, his commentaries and way to explain the contents. Thought the exercises were OK, maybe simpler than I taught but the comments in them helped me a lot to understand the topics. 10/10, a new and better way to teach! Very useful.

Un curso muy bueno, sobre un enfoque de la estadística que desconocía. Además de reforzar muy bien las cosas que ya sabía y darles ese enfoque Bayesiano. Me gusta que todo se resume en la importancia de la probabilidad condicionada, ya que el teorema de Bayes conjuga las probabilidades inversas.

Good to learn or re-learn the basics of statistic and probability, and as a foundation for learning maximum likelihood methods (which are much more useful later on). The material is digestible, to the point, and the quizzes are helpful in checking your understanding and information retention.

A well organized course, learned important concepts in statistics and probability that will definitely help anyone wanting to specialize in machine learning or take up data science. Clear and concise explanation of theory focusing on application that is adequately tested in the exams.

An excellent course on the basics of Bayesian approach to statistics. It has excellent explanations, from the concept to applications and allows gaining understanding both on the basic underlying ideas, as well as a deeper insight on Bayesian methodologies. I definitely recommend it!

I've reviewed probabilities and basic Bayesian methods in this course. The quizzes have good explanation and the additional reading materials are helpful. I'm learning the next course: Techniques and models, which is also great (except that we don't have free access to the quizzes).

As a primer to Bayesian Statistics, this course covers the basics at a brisk pace. No time is wasted in explaining the basics of Probability theory; which I have always found, at best, to be distracting in the other similar courses I have taken. Thank you, Herbert Lee and Coursera.

An interesting course which gives an opportunity not only to study some purely 'technical' skills but also to think a bit about statistical problems in a broader context. It won't make you 'Bayesian', however, it will help to understand the philosophy of this statistical 'sect'.

There are books and courses out there teaching you how to use machine learning tools to solve real problems. But there aren't so many like this starting from the Bayesian way. Besides, this is a good entry point for me to read the book "Pattern Recognition and Machine Learning".

I have signed up for this course because I encountered Bayesian concepts through work (automotive industry), and I wanted to improve my understanding of the underlying basics. What can I say, my expectations have been met! Thanks for offering this course through this platform!

Excellent introductory course to bayesian statistics. I'd like to thank Professor Lee, University of Santa Cruz, Coursera and all supporting staff for the opportunity. I'd enjoy if you provided intermediate and advanced courses on bayesian statistics that covers more topics.

Great course. Very clear introductory overview of Bayesian statistics and differences/similarities with the frequentist approach. Well balanced between video lectures, support materials, quizzes and hands-on problems. Looking forward to the next step - hierarchical models.

It's quite a challenging and informative course. I don't regret taking it it has opened up my mind to Bayesian statistics especially that this is the pass I want to take in my life. Thank you for the support and opportunity given to me. i will forever remain grateful.

I took this course due to my interest in machine learning and graphical models. I like the approach and execution. I recommend it for anyony interrested in statistical inference. Some topics require looking up external sources, like wikipedia, but it is not an issue.

The course was excellent. The concepts were explained very clearly and were supported with well suited quizzes and applications. The course definitely created an interest in learning further in Bayesian Statistics. The instructor was very clear in presenting theory.

This class is very much an intro, so if you're looking for advanced topics you it might not be challenging. But this is a really good intro. The lectures are good and the supplemented material is great. I wish there was more R, but I'm very happy with the class.

Interesting, challenging, informative, entertaining, Herbie Lee is an excellent presenter of a very well prepared introduction to what seems to be a more rational and coherent approach to extracting, understanding and evaluating quantative information from data

It's a great course to understand the fundamentals of the Bayesian Statistics. The easy quiz which meant not to deter the students could be improved a bit. For serious learning, reviewing the questions in honor sections and the supplemental materials is a must.

This course really put into perspective the different approaches of statistics, and how each of them are so valuable. With the aid of the readings given before the lectures, Sir Herbert Lee made the "scary" Math of statistics a little less scary ^-^

This is a short course and it was a great introduction to Bayesian inference. Lessons went through both theory and application. I found the videos easy to follow and that they prepared me for the quizzes. I also really valued learning how to use R.