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
por Deleted A
•9 de jun de 2020
I didn't think the lectures were very good. The instructor wasn't careful with his notation, which was very confusing, and the initial lectures where he used a pastel green marker on a green background and wearing a pastel green shirt made his blackboard text nearly invisible.
However, the assignments were execellent.
por Dmitry S
•20 de set de 2016
The material is good, but I've found the lectures challenging to understand even having some background in math. It would be good if all the definitions and key facts were stated more prominently in the lectures, as opposed to algebraic transformations which most readers can hopefully do on their own.
por Ahmed S
•4 de jan de 2017
This course requires solid grounding in mathematics. No meant of Social Science graduates without proper training in statistics/mathematics. The course was good in the sense that we could how probability distributions are used to model real world problems.
Study material was certainly not adequate.
por Ray P
•14 de jan de 2022
The course presented fundamental concepts of probability, regression, and Bayesian ways of thinking. However, it lacked in applications of Bayesian approaches beyond the most basic. For example, how do we estimate these models on real data to obtain parameters and make inferences or predictions?
por Yuzhong W
•3 de out de 2016
The lectures from week 1 to week 3 are nice and useful to me, but I think there should be more details about the content in week 4. For example, I think the lecture about the Jeffreys prior skipped many things and I did not understand this concept very well.
por Damel L
•29 de nov de 2019
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...
por Olexandr L
•1 de jul de 2017
It was quite difficult to learn from just the material provided here, and I had to look for info on the web. Also, adding modern real life examples and going into detail would make this course better
por Jesús R S
•19 de jul de 2017
Good course as an introduction to bayesian statistics if you want to pursue more advanced courses in the field or to get some practise working with distributions under the bayesian framework.
por Silvia Z
•8 de mai de 2020
In general, the course is useful, but in half of videos the explanation focused mostly on formulas, and less on theory. I personally had difficulty in learning theory of Bayesian statistics.
por Borja R S
•25 de abr de 2020
The teachers are clearly experts in what they do, but sometimes I think it is that same expertise that makes them jump to conclusions too easily, making it difficult for beginners to follow.
por Ran W
•25 de jul de 2020
This course gives a very brief background on conjugate prior. However, the lectures on Bayesian linear regression is too superficial. I wish the lectures could have gone into more detail.
por Carlos
•8 de abr de 2020
Too much time spent on the beginning and too little on later more complicated concepts such as the posterior predictive. It felt as if that was just a side note in the extra readings.
por Augusto S P
•24 de set de 2017
The course is good for beginners in statistics. In my opinion it would be better to invest more time explaining different topics about bayesian regression and bayesian time series.
por Oliver B
•1 de jun de 2020
Solid mathematical grounding, but would have benefited from more time spent on the history of Bayesian inference, when to use it, why it can be used etc..
por Pranav H
•1 de jul de 2018
The course could have given more information on tiny details which can confuse people during the exercises. But overall a good learning experience
por Ángel L
•4 de jul de 2021
It’s ok to have a theoretical basis about Bayesian Statistics, but I missed some practical cases using Python instead of R. I also missed PYMC3
por Kathryn L
•23 de jul de 2021
It's a nice introduction to the topic, but I often found the lectures to be imprecise or inconsistent, especially with respect to terminology.
por Alessandra T
•29 de jun de 2017
We still don't understand how Bayes differs to Frequentist... A worked example comparing the two at the end would have been nice.
por Ken M
•1 de mai de 2019
It would have been great if more graphs had been provided, for easier visualization of the e.g. distributions, or concepts.
por roger
•24 de jul de 2019
It would be better to add more explain about those equations and connect the math stuffs with the real world samples
por Max H
•14 de jul de 2019
It would be much better if there was a more sufficient introduction to the various distributions used in the course.
por Victor D
•9 de jul de 2019
Very informative as an introduction to concepts, but nowhere near the deep dive I'm now interested in taking.
por Isra
•4 de mai de 2020
Good course!!... Additional examples of real life explained and done in R or excel will make it great
por Andres F P A
•18 de jun de 2021
A lot of formulas and not that much interpretation. It is a good start in Bayesian concepts.
por Binu M D
•21 de set de 2019
Too much theoretical than practical applications. No need to give both R and Excel videos.