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Вернуться к Bayesian Statistics: From Concept to Data Analysis

Отзывы учащихся о курсе Bayesian Statistics: From Concept to Data Analysis от партнера Калифорнийский университет в Санта-Крузе

4.6
звезд
Оценки: 2,493
Рецензии: 657

О курсе

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....

Лучшие рецензии

GS
31 авг. 2017 г.

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.

JB
16 окт. 2020 г.

An excellent course with some good hands on exercises in both R and excel. Not for the faint of heart mathematically speaking, assumes a competent understanding of statistics and probability going in

Фильтр по:

201–225 из 645 отзывов о курсе Bayesian Statistics: From Concept to Data Analysis

автор: Xiaoyang G

7 июля 2016 г.

This course is a very good introductory of bayesian statistics. But it better that you have known the basic statistics inference.

автор: Humberto R C

6 нояб. 2017 г.

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

автор: Raj s

8 февр. 2017 г.

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

автор: Tetsuhiko O

20 янв. 2018 г.

I studied basic theory from these lectures. I will try again and again until I understand Baysian Statistics concept completely.

автор: Jose M R F

14 июля 2019 г.

Very well explained. Lectures are given in a very nice way as the professor writes. Exercises and quizzes are very well done.

автор: Zhirui W

25 сент. 2017 г.

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

автор: Eduardo M

4 янв. 2019 г.

Very good material! The Prof explains very easily the contents of the course. Great course! I recommend. E. Martins, Brazil

автор: Leon W

5 авг. 2018 г.

The video content is not too much. However, students can learn and practise a lot from supplementary materials and quizzes.

автор: Salaheldin G

26 дек. 2017 г.

Very useful crash course in Bayesian Statistics. It requires some basic knowledge in statistics and probability as stated.

автор: Miles D R

15 авг. 2019 г.

This course was dense, concise, and yet easy to follow for individuals that are fairly comfortable with basic statistics.

автор: Francisco J S G

26 авг. 2018 г.

A really hard course but useful for those who want to know more about statistics and how it is related to Bayes' theorem.

автор: Álvaro C Q A

27 мар. 2018 г.

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

автор: Jack

17 мая 2018 г.

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

автор: Georgios P

24 февр. 2017 г.

Very good introduction to baysian concepts and very helpful in understanding the difference with frequentist statistics.

автор: Shakir B

3 авг. 2020 г.

Initially I was a bit put off. But what a compilation of well thought set of lectures and quizzes! Thoroughly enjoyed.

автор: Бызов А

27 мая 2018 г.

Marvellous course! Thank you very much! I would really appreciate, if you'll create an advanced version of this course

автор: Flavio P

10 авг. 2017 г.

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

автор: kacl780tr

6 июля 2017 г.

Excellent course, although it would have been nice to get more content on uninformative priors and Fisher information.

автор: 张宁

24 сент. 2016 г.

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

автор: 郭冰

10 мар. 2017 г.

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

автор: Zach K

3 авг. 2020 г.

I learned a ton about statistics and probability distributions. It was great prep for my machine learning classes.

автор: Xilu W

19 нояб. 2016 г.

I'm a graduate student in mechanical engineering. Thanks for the open course, it is really convenient and helpful!

автор: Artur A B

21 авг. 2019 г.

Very useful course, described a basic understanding behind Bayesian theory and sequential updating of posteriors.

автор: Harsh V D

6 авг. 2017 г.

A very well designed and productive course for anyone looking to brush up his/her concepts on Bayesian Statistics

автор: Andrew N

22 окт. 2016 г.

wrote in my comment.

The course is extremely well presented and the difficulty level of the excercises is perfect.