返回到 Bayesian Statistics: From Concept to Data Analysis

4.6

1,809 个评分

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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....

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.

筛选依据：

创建者 Melvyn B

•Jun 02, 2017

Professor Herbert Lee is world-class. The masterful and thoroughly outstanding presentation, organization and content of this activity are among the best of the best in any subject at any institution, whether on campus or otherwise -- more remarkably so for any senior undergraduate to graduate level mathematics activity, and most especially so in the broad field of Bayesian analysis. In summary: Extremely well-done and hats off to Professor Lee. I am thoroughly impressed.

创建者 Albert A M H S

•Jun 29, 2017

Followed the course in order to fill a gap I had in statistics knowledge, as I'm very interested in machine learning - deep learning, and always came upon things as MLE without really knowing well what they were talking all about. Really a very good course to get an understanding! Well explained, though maybe you'll need to brush up your Algebra and Calculus a bit to be able to follow...

创建者 Álvaro Q

•Mar 28, 2018

It's a good introductory course to Bayesian statistics, a second part with Gibbs Sampling, Markov and MCMC would be nice.

创建者 Raj s

•Feb 09, 2017

Learned something new :). Lecture were excellent, but, I need time to digest and hope I will get opportunity to use it in future.

创建者 TERENCE Y

•Sep 19, 2017

An excellent introduction to Bayesian Analysis with some practical examples and applications. The lessons serve as a solid foundation towards understanding the philosophical underpinnings of the Bayesian approach to decision analysis under uncertainty. Thanks to Prof Herbert Lee for making the easy to understand without sacrificing rigour.

创建者 Julian R S

•Nov 15, 2017

A great introduction to bayesian statistics. I warmly recommend this course to those already familiar with the frequentist approach and willing to expand their knowledge.

创建者 Humberto R C

•Nov 06, 2017

A clear and compact introduction. Quizzes and exercises are relevant. I got acces to grades and feedback in the audit one I took.

创建者 Musa J

•Aug 11, 2017

Herbert Lee's Tests are fun (Best!) to learn during the test! Lectures are succinct; Format of writing on the glass towards you and then flipped was right & original. Went on to try Kaggle problems independently. For usable feedback need tiny bit more on Poisson, Gamma, non conjugate intuitively & darker shirts as background.

创建者 Isaac D

•Jan 20, 2017

A step by step course, designed to pay attention all the time with tons of practical examples and very clear explanations, I would definitely recommend it!!

创建者 Guido W R

•Oct 05, 2016

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.

创建者 Manos T

•Jul 19, 2017

Exceptional course on probabilities and statistics from a Bayesian point of view. I would recommend this course to anyone wishing to learn more about probabilities and statistics.

创建者 Flavio P

•Aug 10, 2017

Very interesting. It can help taking notes during the course... to avoid going again through it and take them ex-post.

创建者 Laura B

•Aug 05, 2017

Great course! Well explained with useful additional material. Strongly suggested.

创建者 Rizzardig

•Aug 30, 2016

Just an introduction to the topic but very clear.

创建者 Labmem

•Sep 11, 2016

Good course. This course is quite challenging for people who don't major in math or physics. However, it isn't so difficult to understand as the post half of this course has a lot in common. In my experience, understanding the concept of priors and posterior estimation is the core of this course. Have fun learning this course.

创建者 Kelvin P

•Apr 04, 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.

创建者 BaoYiping

•Sep 06, 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.

创建者 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

创建者 tze s

•Jul 17, 2018

very detailed and good classes on bayesian stats

创建者 郭冰

•Mar 10, 2017

I have learned a lot from this course. As there is not course like this one in my univeristy, I really appreiate it.

创建者 Vimos T

•Aug 25, 2016

This course makes a lot of details clear to me. Thanks professor for this great course.

I still have one question, is the professor writing on a transparent board in inverse pattern? The technique is amazing!

创建者 Martin K

•Feb 24, 2017

Best course yet!

创建者 Sam C

•Jan 15, 2018

Good intro to Bayesian statistics

创建者 Damian C

•Nov 10, 2016

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

Many thanks and congratulations!!!

创建者 Luca M

•May 16, 2017

A concise and clear introduction to the Bayesian paradigm. Its conciseness make it suitable for frequentists wanting to get a quick overview of the Bayesian Way.