Chevron Left
Back to Bayesian Statistics: From Concept to Data Analysis

Learner Reviews & Feedback for Bayesian Statistics: From Concept to Data Analysis by University of California, Santa Cruz

4.6
stars
3,169 ratings

About the Course

This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data. We will learn about the philosophy of the Bayesian approach as well as how to implement it for common types of data. We will compare the Bayesian approach to the more commonly-taught Frequentist approach, and see some of the benefits of the Bayesian approach. In particular, the Bayesian approach allows for better accounting of uncertainty, results that have more intuitive and interpretable meaning, and more explicit statements of assumptions. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience. For computing, you have the choice of using Microsoft Excel or the open-source, freely available statistical package R, with equivalent content for both options. The lectures provide some of the basic mathematical development as well as explanations of philosophy and interpretation. Completion of this course will give you an understanding of the concepts of the Bayesian approach, understanding the key differences between Bayesian and Frequentist approaches, and the ability to do basic data analyses....

Top reviews

GS

Aug 31, 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.

JB

Oct 16, 2020

An excellent course with some good hands on exercises in both R and excel. Not for the faint of heart mathematically speaking, assumes a competent understanding of statistics and probability going in

Filter by:

226 - 250 of 831 Reviews for Bayesian Statistics: From Concept to Data Analysis

By Simiao R

•

Jul 20, 2020

Good course about bayesian! I finally understand the relationship between frequentist idea and Bayesian approach and Beta gamma distributions

By Eben E

•

Apr 12, 2020

This was a were educational course. I had trouble understanding R programming but with this topic, most of the programs became more clear to me.

By Cooper O

•

Jun 27, 2017

A Fantastic course. Detailed learning materials, Lots of opportunities to test your knowledge, and difficult enough to make you learn something!

By Nitin K

•

Jun 1, 2017

I loved everything about this course. It reminded me of my time in school. Papers and pencils. I look forward to attending the follow up course.

By Tiannan S

•

Jul 6, 2020

As a computer science student, I feel Bayesian approach is much more intuitive and more computationally friendly than the frequentist paradigm.

By Fernando D L

•

Mar 11, 2019

It's a good course to know the principal concepts of Bayesian statistics. Also, the course has excellent examples to understand thew concepts.

By O K

•

Mar 2, 2018

I really appreciated the content, and the way it was taught by Prof. Lee. His explanations were intuitive, without loss of mathematical rigour.

By Giovanni G

•

Jul 29, 2020

Consistent and mathematically dense. If you want to go through every passage this course gives you solid understanding of Bayesian statistics.

By Deleted A

•

Dec 15, 2019

Very good course. Concepts are very well explained, and quizzes are really helpful to apply and further

understand the explanations provided.

By Kuntal B

•

Nov 13, 2019

Thanks, Coursera. This is a good course. It would be helpful if we get any proper class notes on Jeffrey's prior and Multivariate regression.

By Artem B

•

Jul 3, 2019

Great course with a lot of simple, but illustrative exercises. It may be useful to have some basic prior knowledge of econometrics/statistics

By Michael W

•

Jan 16, 2019

Great introductory course. It was challenging but doable for someone who has not take college level mathematics or statistics in a few years.

By Robert K M

•

Feb 11, 2018

Invaluable. Excellent quizzes. A few terms could have been better defined, and a few more examples wouldn't hurt, but overall excellent.

By Damian C

•

Nov 10, 2016

Very well presented course. Interesting and intuitive introduction into the fascinating Bayesian world.

Many thanks and congratulations!!!

By Howard H

•

Oct 6, 2021

Excellent introduction to Bayesian statistics -- lectures, readings, and quizzes provide excellent support to learning the main concepts.

By Ariel A

•

Oct 12, 2017

Great course, it has the right proportion of theory and practice. It's a great start for anyone who wants to dive into Bayesian Analysis.

By Hari S

•

Feb 5, 2020

Thought is a simple manner. Made complex concepts look very easy. Would surely recommend this course. Thanks Prof. Herbert Lee and team.

By Vignesh R

•

Oct 8, 2018

Awesome course that helped me overcome the Bayesian statistics way of thinking hurdle. Now, I want to go on and learn MCMC, Metropolis !

By Qinyu X

•

Feb 2, 2020

The course is generally great. Nonetheless, it is not recommended for those without a statistical background and knowledge of calculus.

By Naseera M

•

Feb 12, 2017

Very good course. Prof. Lee explains each concept well. Bayesian Stats makes more sense to me now than before!!

Thanks so much Prof. Lee

By Gustavo C

•

Oct 4, 2018

I loved this course, I learned a lot and I hope I will be able to use this knowledge when I go back to college for my Master's degree.

By Evgenii L

•

May 2, 2018

A very good course. Even better if you continue with the 2nd course that teaches about how to implement Bayesian data analysis in JAGS

By Joseph G

•

Dec 18, 2016

I enjoyed the lecturer, the material is relevant, and the tests are well tailored to ensure you are absorbing the correct information.

By Rodrigo G

•

Jan 16, 2020

Give you great insight. Very intuitive. Although we went through the last week rather quick (more explanation would have been better)

By Jin K K

•

May 13, 2019

The lectures are at the right pace; concise and challenging. Great examples. Thank you so much for providing us with great materials.