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

4.6
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Оценки: 1,880
Рецензии: 488

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

Sep 01, 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.

JH

Jun 27, 2018

Great course. The content moves at a nice pace and the videos are really good to follow. The Quizzes are also set at a good level. You can't pass this course unless you have understood the material.

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26–50 из 477 отзывов о курсе Bayesian Statistics: From Concept to Data Analysis

автор: Paulina S

Mar 10, 2017

This is my first course on Coursera and I am delighted by the construction, how it was led by the instructor and what I learned. Quizzez are great, I spent on some quite a bit of time, but I feel they really checked if I understand the concepts and calculations. The questions during the video are also an excellent idea to check if you follow. All in all I am very happy I took this course!

автор: Kostyantyn T

Aug 04, 2019

I really enjoyed this course, the videos are fairly short with focus on exercises and there is a nice narrative throughout the course. Sometimes I needed to watch videos again because explanations were too fast for me to follow in real time, but I definitely enjoyed presentation style of Prof. Herbert Lee. Will be following the course up with "Techniques and Models" to learn about MCMC.

автор: Albert A M H S

Jun 29, 2017

Followed the course in order to fill a gap I had in statistics knowledge, as I'm very interested in machine learning - deep learning, and always came upon things as MLE without really knowing well what they were talking all about. Really a very good course to get an understanding! Well explained, though maybe you'll need to brush up your Algebra and Calculus a bit to be able to follow...

автор: MaoJie T

Nov 20, 2019

It's a fantastic course, which guides me to know what is Bayesian statistics. Before joining this course, I try my best to learn Bayesian Statistics but it's failed. However, I really grasped some key points and knowledge of Bayesian Statistics and I will join the following course about Bayesian Statistics to get more. Thanks for the professor. I am appreciated for it.

автор: Matteo V

Jun 26, 2017

Great course that introduces the fundamentals of Bayesian Statistics. Useful for becoming familiar enough with the ideas to use in basic analysis provided you have some experience with frequentist statistical methods. For my studies, this course allowed me access to the Bayesian statistical material that is often encountered in phylogenetic analysis in bioinformatics.

автор: Ian M

Aug 16, 2019

I think this was a very helpful course, for me personally I learn better with "real" examples, so i think if there were more of those earlier on, that would have been more helpful. I also use Python, and would prefer to use Python, so it would be nice if there were instructions on that in addition to R/Excel. Spent a lot of time translating between R and Python.

автор: Shubham A

Nov 11, 2017

I strongly recommend this course to those who are interested in learning theoretical concepts that build Machine Learning statistics especially Bayesian. The course content was well organized and the professor presented the concepts in a very engaging way. Relevant and appropriate examples and in-video quizzes were very helpful in understanding the theory.

автор: Ron A

Apr 12, 2017

Excellent course. Professor Lee did a first-rate job of giving the intuition for Bayesian methods and building the foundations for further study of the topic. The course is short and to the point, but that is a feature and not a bug. It will prepare you to take further courses in Bayesian statistics or to study the topic on your own. Highly recommended.

автор: Dennis L W

Sep 17, 2016

Out of 15 online courses I have taken over the last 3 years, this is the best. Professor Lee presents rather difficult material in a clear, detailed, style. The lesson quizzes are remarkably useful; it seems real care has been taken in aligning the questions with the key points in the lectures, and in furthering one's understanding of the same.

автор: Mark S

Feb 08, 2017

I found this course to be really useful. It did progress through the math a bit quickly for my liking, but it was paced very appropriately and the discussion forums were helpful. Excellent examples are contained and I loved how both R and Excel modules were leveraged. Looking forward to seeing more Bayesian courses on Coursera in the future.

автор: David D

Feb 27, 2019

Really loved this course. I am relatively new to Statistics but very familiar with the rest of the mathematical tools used in this class (Integration, sets, etc). After finishing the class, I was immediately able to apply Bayesian Inference to my job. Things were explained well, and made sense after re-watching once or twice. Excellent course!

автор: Polano M

Mar 11, 2018

Great introduction to Bayesian Statistics.

Prof. Lee uses the right approach with a theoretical introduction that helps to graps the concepts with a right balance of math and intuition. This was my first exposure to the bayesian approach to statistics and after this course I want to learn more, both on the pratical and the theoretical side.

автор: TERENCE Y

Sep 19, 2017

An excellent introduction to Bayesian Analysis with some practical examples and applications. The lessons serve as a solid foundation towards understanding the philosophical underpinnings of the Bayesian approach to decision analysis under uncertainty. Thanks to Prof Herbert Lee for making the easy to understand without sacrificing rigour.

автор: Brandon H

Mar 07, 2018

This is a great course! Much better (and cheaper) than the course I took in grad school. Full of practical knowledge, and isn't too overwhelming on the mathematics/statistical theory. It's just right. Good for anyone interested in Bayesian statistics, though some background with probability distributions may help climb the learning curve.

автор: Natasha

Dec 27, 2016

I really enjoyed this course. The lectures were short and clearly explained, and particularly highlighted why Bayesian statistics is different and what is useful about it. I would have like a bit more walk-through on some of the derivations in weeks 3 and 4. More R exercises and further resource recommendations would have been useful.

автор: Galley D

Sep 11, 2017

Outstanding course to understand Bayesian statistics. Teacher is very pedagogical and the course delivery with equations written on the transparent board make everything easy to follow.

As an area for development, I would have like more information on Bayesian linear regression in week 4, through background lecture or dedicated video.

автор: Fedor T

Jan 21, 2017

Very clear lectures masterfully delivered by prof. Lee. The quizzes are good, if somewhat on the easy side. Don't be discouraged by the choice of R as the tool for assignments. R is flawed as a programming language, but you won't need to do any programming, only one-liners to evaluate various statistical functions and plot results.

автор: Nathaniel R

Nov 21, 2016

This is the first online course I have ever taken so I don't have anything to compare it to, but this course was excellent! The lectures and materials were very clear and I will be adopting some of Prof. Lee's approach into my own teaching practice. The bar has been set very high for any future online courses that I will take!

автор: Musa J

Aug 11, 2017

Herbert Lee's Tests are fun (Best!) to learn during the test! Lectures are succinct; Format of writing on the glass towards you and then flipped was right & original. Went on to try Kaggle problems independently. For usable feedback need tiny bit more on Poisson, Gamma, non conjugate intuitively & darker shirts as background.

автор: Labmem

Sep 11, 2016

Good course. This course is quite challenging for people who don't major in math or physics. However, it isn't so difficult to understand as the post half of this course has a lot in common. In my experience, understanding the concept of priors and posterior estimation is the core of this course. Have fun learning this course.

автор: Victor A

Mar 01, 2017

It's a great course, there is a lot of information and it might seem at times overwhelming, but it's organized nicely and prof. Lee has a very comfortable time explaining all the concepts. A few more examples would have made this course easier, but that does not mean it would have been better. It's as good as it gets

автор: John G

Oct 30, 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.

автор: William P

Aug 03, 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.

автор: Guido W R

Oct 05, 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.

автор: Oaní d S d C

Apr 22, 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.