Bayesian Statistics: From Concept to Data Analysis
FREE
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. UC Santa Cruz is an outstanding public research university with a deep commitment to undergraduate education. It’s a place that …
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Courses : 1
Specification: Bayesian Statistics: From Concept to Data Analysis

61 reviews for Bayesian Statistics: From Concept to Data Analysis
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Price  Free 

Provider  
Duration  22 hours 
Year  2016 
Level  Intermediate 
Language  English 
Certificate  Yes 
Quizzes  Yes 
FREE
Michael M –
Very clear and informative. Would like a more extensive and combined reference material (PDF, so less need to lookup e.g. definitions of effective sample size for various distributions).
peiyuan s –
Really good! Thank you
Manuel M S –
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!
Thierry C –
The course was well explained and there were several exercises pushing the learner to understand the logic behind the mathematical concept. I think it is a suitable class for people with already a certain level of statistics knowledge, even though all concepts are well explained.
Lazaros S –
Excellent and very helpful course. Highly recommended
Zhenkai S –
The course is in general well structured. The professor used a lot of mathematical equations to explain the contents. I have no problem understanding them. Everything goes smoothly, until the last section: Bayesian Linear Regression (BLE). In the last section, the professor skipped all the mathematics aspects and rushed the content with R / Excel examples. This is not what I expected. Overall, I will rate the course 4 stars.
Yalong L –
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.
Dave N –
Good fundamentals.
Leandro G G –
This course provides a good overview to Bayesian statistics, but a larger dose of explanations of would be very useful. Mr Lee discusses, in the beginning, the differences between frequentist and bayesian paradigm. I feel that this would be beneficial in the other parts of the course, too. I feel that many of the lectures simply go too fast. After lectures full of Math, it would be useful to present lectures analyzing what had just been taught, in order to better grasp the content. And in general, this happens through the whole course most lectures are basically math, without much time for grasping the intuition and underlying logic. For example: in the final part, under linear regression, it might be be difficult to grasp what a bayesian predictive interval means. All in all, I recommend this MOOC, but you might find hard to fully grasp it.
cuguilke –
I was hoping to get more intuition on bayesian statistics, but I couldn’t. Hence, I think I am gonna forget what I have learned in a very very short time.
Zhen Y –
Very good course! Thank you
Duke W –
Excellent introduction to basic Bayesian analysis and coverage of conjugate priors/posteriors.
Colin J –
A great intro to Bayesian analysis and probability distributions. Personally I skipped the Excel content and converted the R code to python, which was itself valuable learning.
Kuntal B –
Thanks, Coursera. This is a good course. It would be helpful if we get any proper class notes on Jeffrey’s prior and Multivariate regression.
Massimo G –
Very good method and quality of teaching, I’d recommend more solved and commented exercises for each topic exposed, before each week test.
Lucas M –
It was a very nice course that got more practical towards the end. The only thing I found a little bit confusing is the regression part, without theory videos and with practical outcomes that are exactly the same as frequentist approaches. Don’t be discouraged if you come from a background where integers and derivatives are not usual! I come from psychology and I found it a little bit hard at the beginning, but if you put effort you will get to understand almost everything. As long as you get the idea of where things like formulas are coming from and why are they done that way I think it is enough.
Cesar P O –
It needs more examples
Mohd S K –
Course covers the concept in a very simple way. Examples and assignments are very good. However some of the statements made throughout the lectures needs more explanation , the course did not dedicate any videos to get familiar with terminology related to probability.
Steven G –
Very good course.
MaoJie T –
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.
Sina A N –
I would have given this course a zero rating if I could have. The worst online course I had so far. There is no intuition of the subject provided. The instructor just looks like reading from a text (like a robot) and write some equations without enough explanation. There are many Youtube videos available for free that explain concepts way much better than what is available here. Don’t waste your time. Reading a book and watching those Youtube videos would help you more.
Damel –
Most of the support material should be prior reading. Lecturing could be more useful i.e. explaining ore about why we use certain distribution and how to apply them. Most of it as just reciting formulas and felt like a waste of time…
Johan D R P –
This course has been highly useful to understand how hypothesis testing works, starting from experimental design using prior distributions and assumptions to posterior statistics based on data. In my college courses it was always assumed that the parameters for the distribution were fixed, so, having a way to correct them through the information hidden in the data allows to overcome those assumptions and have a clearer perspective of the data behavior.
Mohan R –
A mathematics course I really enjoyed because the instructor was actually teaching the material as best as one could without meeting the students. Great.
Danil G –
It was a good course for me to get familiar with the new perspective on statistics. Thank you! Maybe, some extended practice exercise at the end of the course would make it even better)
Raja G –
The course content is great and provides a good introduction to bayesian statistics. The assignments could be a little more challenging as a lot of the questions require just plugging numbers into formulae.
Xiaomeng W –
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).
RIcardo G M –
Very good course. Concepts are very well explained, and quizzes are really helpful to apply and further understand the explanations provided.
Erkan –
A very nice brief overview of the concept. Good for beginners and for people who want to refresh their memory.
Raj K –
The awesome course really liked the mathematically. If someone really want to understand the Bayesian statistics, they should definitely go through this once.
Sanjay C –
Very well taught.
Jean–Jacques P –
The course is good but requires a lot of homework if you are rusty on probability/statistics…
Jean Jacques P –
The course is good but requires a lot of homework if you are rusty on probability/statistics…
Lukman A S –
The course only gives a lot of equations and formulas without explaining why this process should be done
Bruno M –
I liked the way it was taught, It’s nice for who is looking for to expand data analysis.
zqin –
Overall the class is great, especially the first two weeks’ content is simple and well explained. But from the week 3 to the week 4, the professor only writes many formula and doesn’t provide enough examples to explain those formula.
Eddie C –
Quite harsh but give me some insight on prediction and estimation
Scott B –
Excellent overview of bayesian statistics.
Naehyun P –
Very helpful for understanding the basic concepts of not only Bayesian statistics but also the basic knowledge of statistics, which will be very helpful for understanding other subjects using statistics.
Rodrigo G –
Give you great insight. Very intuitive. Although we went through the last week rather quick (more explanation would have been better)
Ankur S –
Very good course
Taranpreet s –
Assignments are the best part of the code. Videos don’t provide enough conceptual knowledge. Overall considering the intricacies of the topic its a very good course.
Maxim V –
A very thorough into to statistics!
Huaiqing C –
Very good and very clear for me to begin with Bayesian statistics
Soren J –
Excellent course. More R examples. Looking forward to see a course on pymc3 or Tensorflow probability.
Baiyu L –
explanation in details and nice supplementary materials
Qinyu X –
The course is generally great. Nonetheless, it is not recommended for those without a statistical background and knowledge of calculus.
Aditya M –
A great course to learn not only Bayesian Statistics, but covers statistics in general to a great degree. The best part is the exercise, which are almost perfect to learn the course material. After doing tens of MOOCs everywhere, I find this course unique in terms of pushing students to apply the concepts. I loved this course and enjoyed learning with it.
Gowri T –
I liked the quizzes, detailed feedback. The lectures were a bit hurried, but a lot of good content in them.
Hari S –
Thought is a simple manner. Made complex concepts look very easy. Would surely recommend this course. Thanks Prof. Herbert Lee and team.
KUMAR G –
This course has well structured content. Quizzes are also designed in sync with the course. Enjoyed it!!!
Suleyman K –
This is one of the best online courses I took. This is coming from an ex Professor who taught 13 years. The material basic and is brief, but to the point and very well organized and presented. Having some background in statistics helps as some important details are skimped. In a such a short time, I learned well the concept of about Bayesian statistics.
Ezra K –
Good overview of Bayesian statistics.
Alex C –
The last section, normal data, which is very important, could have been instructed in a slower, less hasty way with more details.
Francesco B –
Good introduction to the Bayesian approach to inference. As an introduction, it doesn’t go very deep on some interesting arguments and it leaves out Hierarchical Modeling and estimations through Monte Carlo Markov Chain, but it would have been unfeasible in such a short time. Finally, I would like to point out that mathematical strictness doesn’t mean that the course is too technical: you have just to go through some calculations and review some concepts in order to fully understand them.
Alex T –
Excellent first course in Bayesian statistics definitely not too basic, but just at the right level that you can understand everything in the course without having studied Bayesian statistics before.
Michael D –
the notes for the lectures are missing. In my opinion the notes, which includes the video materials could be very useful. the course was good. I learnt some new concepts in bayesian thinking.
Angelos R –
The teacher has diminished educational qualifications. The topics are simply outlined without further elaboration.
Ezequiel L C –
A good MATHEMATICAL introduction to Bayesian Statistics. I read some of the negative reviews and they claim to have many formulas, well, that was exactly what I was looking because after watching some PyCon Videos about Bayesian Statistics I understood the code to solve the problem but not really why that code works or how. This course may be frustrating for those with no prior introduction to Bayesian statistics, I recommend to take this course after seeing some videos from the Scipy, PyData and PyCon conferences regarding this topic.
Yanlin B –
A great introduction to the world of Bayesian Statistics!
annalise s –
it is a wonderful course. In this course, I have learned some basic theories and concepts for bayesian statistics and also do some applications with R programming. Highly Recommended as a intro courses