返回到 Bayesian Statistics: From Concept to Data Analysis

4.6

1,650 个评分

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435 个审阅

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 Ignacio

•Mar 13, 2018

Very useful course to get an understanding of the ideas behind Bayesian statistics and Bayesian inference. Not your course if you are looking for applied Bayesian inference.

创建者 Andrei B

•Aug 28, 2016

Great course ! Simple and clear !

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 Gaurav a

•Dec 26, 2017

Very encouraging

创建者 Thadeu F

•Jul 05, 2017

Great course. Intermediate to advanced level (at least for me). You must have good foundation in probability. If so, you will learn a lot. Thanks

创建者 Julio C L J

•Jun 12, 2018

It was an excellent course. It´s a very good introduction to the Bayesian approach to inference.

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.

创建者 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.

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 Nguyen Q V

•Aug 21, 2017

It is the good place to start to learn Bayesian theory

创建者 Bijit D

•Sep 20, 2017

A great course on Bayesian Statistics.

创建者 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.

创建者 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!

创建者 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.

创建者 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.

创建者 Liublu B

•Aug 29, 2017

Very good, I reccomend it to data scientist

创建者 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.

创建者 Tomáš B

•Sep 08, 2016

Short, simple and clear explanations. I only regret the course is not longer.

创建者 Mas N

•Jan 18, 2017

Excellent ! Thank you so much !

创建者 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.

创建者 Zhirui W

•Sep 26, 2017

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

创建者 Joe N

•Jan 22, 2017

Great course! Very concise, yet very informative! Go Slugs!