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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
2,820 évaluations
734 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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76 - 100 sur 726 Avis pour Bayesian Statistics: From Concept to Data Analysis

par Kevin L

24 mai 2020

This is a great course for anyone with no prior knowledge of Bayesian statistics. The instructor did a great job explaining the concepts and provided good examples. I also liked the quizzes and activities in R/Excel. I learned a lot from this course! I plan to take a few more courses in Bayesian stats.

par John G

30 oct. 2017

Prof Lee derived the formulas in an upbeat way, which helped me learn. I'd suggest putting the actual lectures into pdf for later reference, like is done for supplementary material. Homework assignments were challenging and educational. You might suggest a review of prob distributions as pre-requisite.

par William P

3 août 2018

Fantastic first course. The only concern I have is with the software choices. I have neither R nor Excel, but was able to easily use google Sheets. It might be worth mentioning to students that this is an option. There is even a stats package that claims parity with one of the listed packages for excel.

par José R

23 août 2020

The quizzes in the course are very well elaborated and designed to help you learn points and details not explicitly stated in the lectures. The contents and pacing are just about right for me. Perhaps the section on normal inference would need more elaborated as this part was the most difficult for me.

par Najib B

26 août 2021

This course provide the theoretical basics for anyone who wants to understand, and hopefully work with, Bayesian stats. Prof. Lee's exposition of the math behind Bayesian stat is precise concise and to the point. If I, with only high school math from age ago, could understand, I believe anyone can.

par Guido W R

5 oct. 2016

Very nice course that in my opinion nicely fits between Bolstad and Gelman in difficulty (talking in popular Bayesian Data Analysis books). Herbert Lee does a very good job at building one's intuition and understanding in the general Bayesian inference. Good starting point for moving on with Bayes.

par Oaní d S d C

21 avr. 2018

Amazing. Simple, fast, dense, very well taught. I loved the professor, his commentaries and way to explain the contents. Thought the exercises were OK, maybe simpler than I taught but the comments in them helped me a lot to understand the topics. 10/10, a new and better way to teach! Very useful.

par Erick S O B

27 sept. 2020

Un curso muy bueno, sobre un enfoque de la estadística que desconocía. Además de reforzar muy bien las cosas que ya sabía y darles ese enfoque Bayesiano. Me gusta que todo se resume en la importancia de la probabilidad condicionada, ya que el teorema de Bayes conjuga las probabilidades inversas.

par Derek H

12 juin 2019

Good to learn or re-learn the basics of statistic and probability, and as a foundation for learning maximum likelihood methods (which are much more useful later on). The material is digestible, to the point, and the quizzes are helpful in checking your understanding and information retention.

par Devesh S

30 juin 2017

A well organized course, learned important concepts in statistics and probability that will definitely help anyone wanting to specialize in machine learning or take up data science. Clear and concise explanation of theory focusing on application that is adequately tested in the exams.

par Manuel M S

29 avr. 2020

An excellent course on the basics of Bayesian approach to statistics. It has excellent explanations, from the concept to applications and allows gaining understanding both on the basic underlying ideas, as well as a deeper insight on Bayesian methodologies. I definitely recommend it!

par Xiaomeng W

13 déc. 2019

I've reviewed probabilities and basic Bayesian methods in this course. The quizzes have good explanation and the additional reading materials are helpful. I'm learning the next course: Techniques and models, which is also great (except that we don't have free access to the quizzes).

par Sujith N

24 févr. 2018

As a primer to Bayesian Statistics, this course covers the basics at a brisk pace. No time is wasted in explaining the basics of Probability theory; which I have always found, at best, to be distracting in the other similar courses I have taken. Thank you, Herbert Lee and Coursera.

par Mikhail G

6 juin 2020

An interesting course which gives an opportunity not only to study some purely 'technical' skills but also to think a bit about statistical problems in a broader context. It won't make you 'Bayesian', however, it will help to understand the philosophy of this statistical 'sect'.

par liqul

27 avr. 2019

There are books and courses out there teaching you how to use machine learning tools to solve real problems. But there aren't so many like this starting from the Bayesian way. Besides, this is a good entry point for me to read the book "Pattern Recognition and Machine Learning".

par Eric L

13 juin 2020

I have signed up for this course because I encountered Bayesian concepts through work (automotive industry), and I wanted to improve my understanding of the underlying basics. What can I say, my expectations have been met! Thanks for offering this course through this platform!

par Angelo F

8 janv. 2017

Excellent introductory course to bayesian statistics. I'd like to thank Professor Lee, University of Santa Cruz, Coursera and all supporting staff for the opportunity. I'd enjoy if you provided intermediate and advanced courses on bayesian statistics that covers more topics.

par Christos H

8 janv. 2021

Great course. Very clear introductory overview of Bayesian statistics and differences/similarities with the frequentist approach. Well balanced between video lectures, support materials, quizzes and hands-on problems. Looking forward to the next step - hierarchical models.

par chipo n

31 août 2020

It's quite a challenging and informative course. I don't regret taking it it has opened up my mind to Bayesian statistics especially that this is the pass I want to take in my life. Thank you for the support and opportunity given to me. i will forever remain grateful.

par Marcin K

23 sept. 2017

I took this course due to my interest in machine learning and graphical models. I like the approach and execution. I recommend it for anyony interrested in statistical inference. Some topics require looking up external sources, like wikipedia, but it is not an issue.

par Chandanie N

26 déc. 2020

The course was excellent. The concepts were explained very clearly and were supported with well suited quizzes and applications. The course definitely created an interest in learning further in Bayesian Statistics. The instructor was very clear in presenting theory.

par Quinn

18 mars 2017

This class is very much an intro, so if you're looking for advanced topics you it might not be challenging. But this is a really good intro. The lectures are good and the supplemented material is great. I wish there was more R, but I'm very happy with the class.

par Clive S H

15 janv. 2018

Interesting, challenging, informative, entertaining, Herbie Lee is an excellent presenter of a very well prepared introduction to what seems to be a more rational and coherent approach to extracting, understanding and evaluating quantative information from data

par Ying L

3 juil. 2017

It's a great course to understand the fundamentals of the Bayesian Statistics. The easy quiz which meant not to deter the students could be improved a bit. For serious learning, reviewing the questions in honor sections and the supplemental materials is a must.

par Danysh S

2 févr. 2021

This course really put into perspective the different approaches of statistics, and how each of them are so valuable. With the aid of the readings given before the lectures, Sir Herbert Lee made the "scary" Math of statistics a little less scary ^-^