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

4.6
звезд
Оценки: 2,722
Рецензии: 710

## 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

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## 151–175 из 698 отзывов о курсе Bayesian Statistics: From Concept to Data Analysis

автор: Manos T

19 июля 2017 г.

Exceptional course on probabilities and statistics from a Bayesian point of view. I would recommend this course to anyone wishing to learn more about probabilities and statistics.

автор: Magdalena S

7 дек. 2016 г.

One of the best courses I took to date. Paralleled only by ML (by Andrew Ng). Non-trivial assignments, focused on practice, well-explained concepts in readings. Truly impressed.

автор: Oleksii N

25 авг. 2020 г.

The best course for beginners in Bayesian analysis! But some knowledge of frequentist statistics, distributions (Exponential, Poisson, Normal, Bernoulli, Binomial) is required.

автор: Jaime E A T

7 мар. 2019 г.

I recommend this course for anyone interested in learning Bayesian statistics: You can start here. It covers the core concepts as well as some computations using R and Excel.

автор: Deepak K

17 сент. 2017 г.

Very well structured course. Problems and quiz are real life problems, and it's challenging and rewarding to solve them. Thanks to Prof. Lee for delivering an awesome course.

автор: Enrique s c

11 нояб. 2020 г.

La explicación del material y lecciones fueron excelente. El contenido me agrado, aunque mi recomendación sería que fuera un poco más formal las definiciones. Lo recomiendo.

автор: Ignacio

13 мар. 2018 г.

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.

автор: Jian C

21 сент. 2020 г.

I really enjoyed this course. The instructor explained the concepts concisely and clearly. The information was useful, the supplementary materials and quizzes were helpful.

автор: Mohan N

3 мар. 2018 г.

Alot of information, concise and clarity is awesome. Would recommend this course to anyone. And I did too. Great, professor. My only suggestion is to speak a little slower.

автор: Timo K

13 мар. 2019 г.

Very good overview to the area. Efficient and clear lectures - emphasis on the quizzes that required just a proper amount of focus and time from my personal point of view.

автор: Maurice

27 апр. 2020 г.

Presenter is awesome. Just the right pace - and very clear. Material is well thought of.

Only latex formula's don't show up that nice in Chrome... Had to switch to Safari.

автор: Julian R S

15 нояб. 2017 г.

A great introduction to bayesian statistics. I warmly recommend this course to those already familiar with the frequentist approach and willing to expand their knowledge.

автор: Dariia V

7 мая 2019 г.

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!

автор: KJ B

14 июля 2017 г.

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.

автор: Marc N E D

13 мар. 2020 г.

Very good and concise course. I would, however, propose to delve more into theoretical mathematics and explain them with more detail as it seemed to advance very fast.

автор: Quan N

2 авг. 2017 г.

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.

автор: Brian K

19 февр. 2019 г.

Great introduction to Bayesian statistics. Very helpful for me, especially for understanding some of the times when priors might be useful, and how they can aid me.

автор: Frank K

1 июля 2017 г.

Taking this course hase been fun. The material is presented in a clear and structured way, the Tests help to understand and deepen the knowledge. I can recommend it.

автор: Sankarshan M

27 авг. 2017 г.

very good course with good concept and work. Content is very rich. Assignments are very good. It was very helpful for me. Thanks for providing such a good course.

автор: Neal S

10 апр. 2020 г.

Overall a great course! The honors assignments helped deepen the understanding of the concepts, and weren't just extra work.

The instruction videos are a bit dry.

автор: ENRICO S

17 авг. 2017 г.

Great course. I was more confident in frequentist than Bayesian one so, I found this course very enlightening for me and topics' structure has never been boring.

автор: Pat B

1 авг. 2017 г.

Necessary concepts are reviewed to the necessary depth. This is a rigorous yet light material that presents statistics on university intermediate/advanced level.

автор: Luca M

16 мая 2017 г.

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.

автор: BÙI T H

2 дек. 2017 г.

Thank you so much, Herbert Lee. I really like the way you explain everything clearly and how you organizes the contents. I recommend this course for my friends.

автор: Elma J

11 мая 2020 г.

excellent course to understand Bayesian approach. i have good idea bout prior and posterior probability, predictive distribution , maximum likelihood estimates