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Voltar para Bayesian Statistics: From Concept to Data Analysis

Comentários e feedback de alunos de Bayesian Statistics: From Concept to Data Analysis da instituição Universidade da Califórnia, Santa Cruz

4.6
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2,933 classificações
762 avaliações

Sobre o curso

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....

Melhores avaliações

GS

31 de ago de 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.

JB

16 de out de 2020

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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601 — 625 de 755 Avaliações para o Bayesian Statistics: From Concept to Data Analysis

por Arthur M

30 de mar de 2018

Very good introduction to bayesian statistics, but I would have liked a bit more written material to complement the videos, who were rather short and fast.

por Víthor R F

12 de jan de 2018

It is interesting learning the mathematics behind the analysis, but it could have been more complete, with a little less theory and more data analysis.

por xu w

2 de set de 2017

this is a very good introductory course on Bayesian Statistics. Thought you will not learn deep from this course, it will give you a good big picture.

por Tuhin S

1 de set de 2017

Great course with easy to understand examples. One can explore deeper into the world of Bayesian statistics after completing this preliminary course.

por Bae,Bongsung

8 de set de 2020

All the weeks were great, but the week 4 seems to be in complete and lack of explanations. Some refinement on the week 4 materials would be great.

por Yalong L

10 de out de 2019

The first question in Week 4 Honor Quiz, the coefficient for intercept, I got 138 which you show incorrect, would like to know the correct answer.

por Taylor J W

1 de jan de 2018

Very good intro to Bayesian statistics. I only rate 4/5 because the second week was disproportionately more difficult than the other three weeks.

por Deleted A

27 de ago de 2017

I've always found stats kind of boring but, the material covered in this course is invaluable. Dr. Lee presents everything clearly and concisely.

por Philippe B

28 de dez de 2020

Great! Clear, systematic... but: requires a good basic knowledge of mathematics and lacks practical examples to illustrate the models presented

por Việt P H

28 de jun de 2020

A nice course. I gave me a fundamental knowledge about Bayesian Statistics. The lectures are sometime a bit confusing but overall, it's great.

por Sydney W

18 de ago de 2020

more examples of solving problems would have help. or having direct references to sources that explain the technical aspects of the material.

por Seth T

11 de dez de 2020

The course could use slightly more explanation of how Bayesian statistics is applied to real world problems (vs. frequentist application).

por Massimo G

17 de nov de 2019

Very good method and quality of teaching, I'd recommend more solved and commented exercises for each topic exposed, before each week test.

por Xu Z

7 de abr de 2017

Very concise and easy to follow to the end. The linear regression part could be more clear (i.e., with a lecture on the background).

por Alex C

17 de fev de 2020

The last section, normal data, which is very important, could have been instructed in a slower, less hasty way with more details.

por Björn A

21 de jun de 2020

Great course to get acquainted with Bayesian statistics and inference. Just wished seeing a bit more of mathematical background.

por David L

28 de nov de 2018

Need more information about linear regression, given material is not enough to understand topic and effectively find solution.

por Ethan V

2 de nov de 2017

A bit dry overall, but I appreciate the rigor and precision, along with the practical examples in R. I learned a great deal.

por Sameer G

4 de nov de 2017

Hi , this course opened a door for me in Data analysis. Very intuitive & must course for any person exploring data science.

por Jan J

28 de ago de 2019

Good course, but it could really use some PDFs with lecture notes ( as in contents of videos, not supplementary material).

por abhisingh03

14 de jan de 2017

This course has given me some good new insights into perceiving data and has got me started nicely I am very great full.

por Leonardo G Z

29 de jun de 2021

Overall the course is nice for the basics. However, I expected a little bit more coding and less mathematical formulas.

por Jakob L

16 de mar de 2019

Good introduction and interesting topics. However, some of the model analyses are not appropriate and feels artificial.

por Rohit J

4 de fev de 2018

As a graduate student pursuing Machine Learning, this was a great course for me to get introduced to Bayesian Models.

por tommaso c

23 de nov de 2021

D​ifficult to work on assignments because it was unclear how to implement the knowledge discussed during the lecture