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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
3,170 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

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126 - 150 of 831 Reviews for Bayesian Statistics: From Concept to Data Analysis

By Alysa

Jun 4, 2017

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.

By Kelvin P

Apr 4, 2017

I really like the assignments, they are very well designed and helped a lot in consolidating my understanding of the topic. In my opinion, these assignments are the reason why coursera courses are better than the video lectures available elsewhere.

By 来健 张

Oct 30, 2021

Excellent course with lots of facinating exercises of real world applications! Learning from doing!! Can't love the course more!!

However, the difficult part was left with no explanation. But this is helpful for the starter of baysian statistics.

By Francisco C

Sep 22, 2017

Excellent introduction to Bayesian inference. Dr. Lee struck an exceptional balance between presenting concepts and ideas with self-learning through the homework quizzes. I look forward to learning more analysis techniques in subsequent courses!

By BaoYiping

Sep 5, 2016

it's very helpful for me to understand the Bayesian statistics. things are clearly stated and the quiz are good. Many thanks! It's better to have a further course on the Monte Carlo. It's better if the regression can be talked more in details.

By Ruoxiao S

Aug 15, 2019

This class is pretty helpful for the beginners and the instructor has a clear organization of the lecture. The Quizzes are also a good way to know what you have mastered. I have a better and deeper understanding of the Bayesian Statistics now.

By Nicholas P

Jan 13, 2018

Highly informative. Prof. Herbert Lee is a great professor providing very thorough notes and material for the Bayesian paradigm of Statistics. I would highly recommend this to any who are interested. It is also a great introduction to using R.

By Michail L

Aug 4, 2019

It was an amazing course. Prof. Lee is an excellent teacher, the lectures were very interesting and illuminating, and the problems challenging and based on the material discussed. Highly recommended to get a basic idea of Bayesian statistics.

By Kilder U

Jul 25, 2020

A good introduction to Bayesian Statistics. Not too deep, but you need to have some familiarity with probability notation. Also it seems it recently had some manteinance because broken links in lectures are now redirected to correct links.

By Jason R

Apr 8, 2017

I found this course to be incredibly useful to learn Bayesian statistics and a useful guide for applying the information in r and excel. I would definitely recommend it to anyone interested in furthering their understanding on this topic.

By Juan J O O

Jun 6, 2019

Excellent course. I learned late to use the note clipboard to take notes. At times the video lectures are hard to follow because the concepts are not easy. I had to watch the video lectures several times to fully grasp the concepts.

By Luca A

Sep 22, 2018

Really interesting course, expecially in the first part, which has a simple and clear introduction where the "philosophy" of Bayesian approach is explained. Now I have some useful instrument and the curiosity for more sophisticated ones.

By Ayush T

Feb 18, 2019

It's really a good course for Bayesian Statistics. Exercises are designed in such a way that they can't be passed if you've not understood the topic completely. The workload is manageable and the course content is really well organized.

By Ghanem w

Feb 14, 2017

This course provide a very good understanding of the bayesian approach of the statistic. It is very accessible thanks to the learning material (pdf) provided before each lessons and which recall all the basis needed.

Thank you Herbie

By Syarif M

Dec 2, 2016

Definitly the best statistic course for beginners with some mathematical knowledge. Love the way the videos are recorded (Transparent glass between the camera and teacher) it should be a standard for online course! thank you so much!

By Andre M P

Jul 21, 2021

Great course. It gives you a nice view from Bayesian statistics and the understanding of priors, conjugates and posterior. Also great that it uses R for some practical coding (it also shows how to do in Excel, but R is much better)

By Howard H

Apr 10, 2018

A very solid introduction to Bayesian Statistics. Lectures were sufficiently detailed and of excellent quality, and the problem sets supported and reinforced the material very well. I look forward to taking part 2 of this sequence.

By Filip K

Aug 2, 2023

A solid, broad overview of Bayesian fundamentals. This course involves some math; if you are comfortable integrating polynomial functions and have some exposure to probability distributions, you will get a lot out of this class.

By Muhammad Z R

Mar 27, 2021

If variables be consistent throughout all lectures, it would be great.

Shirt color was matching at some instances due to which seeing notes on lecture board was difficult.

Examples and quizzes were quite helpful for understanding.

By Benny T

Aug 15, 2023

Love the presentation style on the board (not a PPT-like style). Worthwhile for those who want to get familiarise the analytic form of probability distribution in Bayesian update. Lots of exercises that train up your sense :)

By Y. N

Mar 5, 2023

Love the course. All concepts and equations written out clearly.

One suggestion: a few things, like the normal and inverse-gamma conjugate, that could have more detailed derivations instead of just giving the final results.

By Sergio D H

Sep 21, 2017

Great introductory course on Bayesian data analysis. The course is self-contained and the videos make a great job explaining the concepts of each lesson. I truly appreciated the practical approach either with R or Excel.

By Alejandro D O

Mar 3, 2020

Excellent course. Prof. Lee is a superb teacher. The balance between class, exercices and tests is well achieved. I would certainly recommend this course to anyone aiming for a first encounter with Bayesian statistics.

By Sandro P

Nov 21, 2017

Very interesting course.

For me the most interesting and important themes are about priors:

1) conjugated priors

2) effective prior size

3) how to choose a prior

4) non-informative priors

5) improper priors

6) Jeffreys priors

By joari c

Feb 9, 2017

Very instructive introduction to Bayes reasoning. By attending all videos and completing quizzes, you get a reasonable understanding of the concepts and reasoning. Thanks to prof Herbert Lee and all the supporting team