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Avis et commentaires pour d'étudiants pour Bayesian Statistics: From Concept to Data Analysis par Université de Californie à Santa Cruz

4.6
étoiles
2,857 évaluations
743 avis

À propos du cours

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....

Meilleurs avis

GS
31 août 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 oct. 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 sur 737 Avis pour Bayesian Statistics: From Concept to Data Analysis

par Björn A

21 juin 2020

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

par David L

28 nov. 2018

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

par Ethan V

2 nov. 2017

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

par Sameer G

4 nov. 2017

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

par Jan J

28 août 2019

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

par abhisingh03

14 janv. 2017

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

par Leonardo G Z

29 juin 2021

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

par Jakob L

16 mars 2019

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

par Rohit J

4 févr. 2018

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

par tommaso c

23 nov. 2021

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

par Yixuan C

2 janv. 2022

T​he material is quite hard for someone who has only basic knowledge in statistics. But the excercises are helpful.

par Muksitul I

2 juil. 2018

Well explained and articulated. You can apply it straight to your work problems. I really enjoyed doing the course.

par Sankar M

21 juin 2020

Excellent introductory course. Some of the concepts in the later part of the course are not explained well though.

par Robert G

3 juil. 2019

Overall great course, the last part (linear regression) seems somewhat disconnected from the rest of the course.

par lai p w

1 janv. 2018

I can learn the concept, but need to understand the details well in other ways. eg. reading, or searching online

par Jose a z r

28 août 2017

Very helpfull course. I will use the principles taugh for other topics like machine learning. Thans for sharing.

par Jan B

3 oct. 2020

Great course with a good theory/practice balance, but examples could be a bit more refreshing and less boring.

par Pranesh K

10 mars 2017

The course is excellent to learn all the basic stuff needed to master the technique of Bayesian Data Analysis.

par Guruprasad K

25 juin 2020

More assignments and live and truncky examples applying the principles would make course even more wonderful

par Somnath C

3 déc. 2016

I wish the last week were more explanatory. Although overall now I do have an idea. It's a good course. :-)

par Sarah D

4 août 2020

Could do with more exercises.

However, I found some elsewhere on the internet, so that was complementary

par Marco

30 juil. 2020

Pretty good introductory material overall. Only disappointing part was the section on linear regression.

par Sergio

30 sept. 2018

Very nice introductory course, practical and to the point. Good starting point for more detailed courses

par Mangmang Z

11 janv. 2018

A little hurry in the normal distribution part, otherwise a great course for Bayesian introduction.

par Vinicius M E M

22 juil. 2021

Excelente curso, porém acredito que uma implementação dos códigos também em Python seria perfeito.