Bayesian Statistics: From Concept to Data Analysis に戻る

4.6

1,527件の評価

•

406件のレビュー

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....

by GS

•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.

by JH

•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.

フィルター：

395件のレビュー

by Eugene Brusilovskiy

•May 22, 2019

Excellent instructor and very helpful readings and assignments.

by Jenna Kwon

•May 13, 2019

The lectures are at the right pace; concise and challenging. Great examples. Thank you so much for providing us with great materials.

by Cem Tabakci

•May 11, 2019

It was a groundbreaking course. I highly suggest it.

by Borisov Vadim

•May 10, 2019

I like this course, thank you!

by Dariia Vyshenska

•May 07, 2019

simple, clear and enjoyable. will take the second course in the series, then move to heavy literature on the topic.

Special thank you to the instructor! you are amazing!

by Yahia El Gamal

•May 04, 2019

Very good course for beginning bayesian inference. The syllabus is easy to follow, but I also think one could benefit even more by complementing the lectures with other sources (books or other youtube explanation)

by Ken Moriyama

•May 01, 2019

It would have been great if more graphs had been provided, for easier visualization of the e.g. distributions, or concepts.

by Adam Sorini

•May 01, 2019

This course is great! Very clear, very professional, and lots of useful content!

by Vítor Ramos

•Apr 29, 2019

The practice exercises were very well conceived!

by liqul

•Apr 28, 2019

There are books and courses out there teaching you how to use machine learning tools to solve real problems. But there aren't so many like this starting from the Bayesian way. Besides, this is a good entry point for me to read the book "Pattern Recognition and Machine Learning".