返回到 Bayesian Statistics: From Concept to Data Analysis

4.6

1,784 个评分

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461 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 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.

创建者 Syarif M

•Dec 02, 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!

创建者 Quanying L

•Jun 29, 2018

The course is informative and clear. Thanks.

创建者 Gu F

•Feb 16, 2017

amazing quizes, and you don't have pay to take them.

创建者 howcanimove@gmail.com

•Jan 21, 2017

Very useful lesson! give me a new perspective on daily data analysis.

创建者 Juan M R

•Aug 26, 2017

It is very useful to acquire a basic knowledge about Bayesian statistic.

创建者 Devesh S

•Jun 30, 2017

A well organized course, learned important concepts in statistics and probability that will definitely help anyone wanting to specialize in machine learning or take up data science. Clear and concise explanation of theory focusing on application that is adequately tested in the exams.

创建者 Roderick R

•Apr 12, 2017

Excellent course!!

创建者 Kelvin L

•May 31, 2017

Very informative and challenging course.

创建者 Dr. R M

•Nov 15, 2017

Very informative and clear presentation of the material, which makes it fun and quick to learn the topics. Very good quiz questions.

创建者 matthew

•Jul 30, 2017

I strongly recommend this course. Clear structure and insightful questions. Thanks for instructor's inputs.

创建者 Sergio G

•Jul 25, 2017

Wow!!! it was great!

创建者 Antoine N

•Aug 21, 2017

Great introduction to the Bayesian framework! The exercises are relevant and I look forward to the second part (Bayesian Statistics: Techniques and Models).

创建者 Sean E

•Mar 12, 2018

Great introduction to Bayesian Statistics with some easy-enough-to-follow mathematical insights.

创建者 Ying L

•Jul 03, 2017

It's a great course to understand the fundamentals of the Bayesian Statistics. The easy quiz which meant not to deter the students could be improved a bit. For serious learning, reviewing the questions in honor sections and the supplemental materials is a must.

创建者 Georgi S

•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.

创建者 Brian J

•Mar 18, 2018

Great course, I learned a lot. Challenging!

创建者 Paulina S

•Mar 10, 2017

This is my first course on Coursera and I am delighted by the construction, how it was led by the instructor and what I learned. Quizzez are great, I spent on some quite a bit of time, but I feel they really checked if I understand the concepts and calculations. The questions during the video are also an excellent idea to check if you follow. All in all I am very happy I took this course!

创建者 Anupam K

•Mar 16, 2018

Extremely useful course. The way concepts are taught is amazing. However, if you are like me, you will have problems following the lectures at the speed at which the professor proceeds. It's a minor 'subjective' issue. The second issue is that sometimes, the equations in the quizzes may appear in the form of "cryptic codes", for the lack of better words, and you'll know it if you face it. A change of browser solves the problem, for me a shift from Chrome to Safari did the trick! Hope this helps.

创建者 Jack

•May 17, 2018

The teacher is excellent and charming and the course is also easy to follow. However, with more exercise will be better!

创建者 A F

•Apr 21, 2018

Great explanations, with detailed steps to follow.

创建者 Clive S H

•Jan 15, 2018

Interesting, challenging, informative, entertaining, Herbie Lee is an excellent presenter of a very well prepared introduction to what seems to be a more rational and coherent approach to extracting, understanding and evaluating quantative information from data

创建者 KJ B

•Jul 14, 2017

This is a good course. The instructor offers additional material that help with the understanding of the material, along with enough quizzes to help with practical use.

创建者 Madhu S

•Feb 17, 2018

Nice introductory course. Some mathematics skills needed to fully appreciate.

创建者 Evgenii L

•May 02, 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