Bayesian Statistics: From Concept to Data Analysis(으)로 돌아가기

4.6

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451개의 리뷰

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.

필터링 기준:

교육 기관: 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.

교육 기관: 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.

교육 기관: Quan N

•Aug 02, 2017

This course helped me a lot in getting a better understanding of Bayesian methods. I recommend this course for all data scientists and machine learning practitioners.

교육 기관: 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.

교육 기관: Marcin K

•Sep 23, 2017

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.

교육 기관: 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.

교육 기관: 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.

교육 기관: Fabian M

•Feb 20, 2018

The course manages very well to balance out comprehensibility and content. Professor Herbert Lee has obviously prepared the material very thoroughly and imparts the content of the course in an enjoyable fashion.

교육 기관: Liublu B

•Aug 29, 2017

Very good, I reccomend it to data scientist

교육 기관: 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.

교육 기관: 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.

교육 기관: Sujith N

•Feb 24, 2018

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.

교육 기관: 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.

교육 기관: Zhirui W

•Sep 26, 2017

Become very clear about all the formula and derivation of Bayesian Statistics after taking this course. Strongly recommended.

교육 기관: Laura B

•Aug 05, 2017

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

교육 기관: 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.

교육 기관: 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

교육 기관: 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.

교육 기관: 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!!

교육 기관: 张宁

•Sep 24, 2016

This course are excellent and Thanks for Prof for offering the course. I've learned a lot from the course. Thank you.

교육 기관: Nguyen Q V

•Aug 21, 2017

It is the good place to start to learn Bayesian theory

교육 기관: Bijit D

•Sep 20, 2017

A great course on Bayesian Statistics.

교육 기관: Fedor T

•Jan 21, 2017

Very clear lectures masterfully delivered by prof. Lee. The quizzes are good, if somewhat on the easy side. Don't be discouraged by the choice of R as the tool for assignments. R is flawed as a programming language, but you won't need to do any programming, only one-liners to evaluate various statistical functions and plot results.

교육 기관: Nathaniel R

•Nov 21, 2016

This is the first online course I have ever taken so I don't have anything to compare it to, but this course was excellent! The lectures and materials were very clear and I will be adopting some of Prof. Lee's approach into my own teaching practice. The bar has been set very high for any future online courses that I will take!

교육 기관: 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!