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Вернуться к Bayesian Statistics: Techniques and Models

Отзывы учащихся о курсе Bayesian Statistics: Techniques and Models от партнера Калифорнийский университет в Санта-Крузе

4.8
звезд
Оценки: 301
Рецензии: 87

О курсе

This is the second of a two-course sequence introducing the fundamentals of Bayesian statistics. It builds on the course Bayesian Statistics: From Concept to Data Analysis, which introduces Bayesian methods through use of simple conjugate models. Real-world data often require more sophisticated models to reach realistic conclusions. This course aims to expand our “Bayesian toolbox” with more general models, and computational techniques to fit them. In particular, we will introduce Markov chain Monte Carlo (MCMC) methods, which allow sampling from posterior distributions that have no analytical solution. We will use the open-source, freely available software R (some experience is assumed, e.g., completing the previous course in R) and JAGS (no experience required). We will learn how to construct, fit, assess, and compare Bayesian statistical models to answer scientific questions involving continuous, binary, and count data. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience. The lectures provide some of the basic mathematical development, explanations of the statistical modeling process, and a few basic modeling techniques commonly used by statisticians. Computer demonstrations provide concrete, practical walkthroughs. Completion of this course will give you access to a wide range of Bayesian analytical tools, customizable to your data....

Лучшие рецензии

JH

Nov 01, 2017

This course is excellent! The material is very very interesting, the videos are of high quality and the quizzes and project really helps you getting it together. I really enjoyed it!!!

KD

Jan 09, 2020

Excellent teacher and very well taught. Right amount of theory and programming combination. Made the subject easy to learn. Enjoyed it very much. Thank you very much.

Фильтр по:

51–75 из 86 отзывов о курсе Bayesian Statistics: Techniques and Models

автор: Víthor R F

Apr 10, 2018

Very cool, probably the best course I've done in Coursera. Keep rocking! :)

автор: Gustavo M

Aug 26, 2019

Very nice course. A bit more theory on sampling methods would be welcome.

автор: Alejandro D O

May 13, 2020

Excellent, balanced (theory and practice) course. I enjoyed very much.

автор: Nicholas W T

Sep 06, 2018

Very thorough instruction. Excellent feedback and support on forums.

автор: Ahmed M

Nov 12, 2018

If you want to become good in modelling it is recommended to enrol.

автор: Stephen B

May 30, 2019

Best course done to date. I wish they had one in STAN too!

автор: nicole s

Nov 07, 2017

A great course, very detailed and a very good instructor!

автор: Ilia S

Sep 24, 2018

I found this course very interesting and informative.

автор: Ken A

Jan 27, 2020

Excellent course. Streamlined but extremely useful.

автор: Hsiaoyi H

Jul 31, 2018

Great course to learn both theories and techniques!

автор: Arkobrato G

Nov 11, 2019

Great course with challenging assignments and de

автор: Lau C

Apr 15, 2019

Super clear and easy to follow. Thanks so much.

автор: Tibor R

Apr 20, 2019

Very good and useful course, and hard as well.

автор: Victor Z

Jul 30, 2018

A very good practical and theoretical course

автор: Farrukh M

Jul 25, 2017

I appropriate the way the course is taught.

автор: Evgenii L

May 02, 2018

A very good course to introduce yours

автор: Luis H

Jul 30, 2017

Rather useful and easy understanding

автор: JOSE F

Feb 11, 2018

Very challenging but interesting!

автор: Nikola M

Apr 07, 2019

one of best stats courses I had

автор: Chen N

Apr 08, 2019

Amazing, super cool!

автор: Luis A A C

Jun 06, 2019

Excellent course.

автор: Thaís P M

Jul 01, 2017

Very good curse!!

автор: Sameen N

Apr 30, 2020

Amazing course.

автор: Harshit G

May 09, 2019

Great course.

автор: Michael B R

Dec 29, 2017

Great course!