Sep 21, 2017
Great course. Difficult to apprehend sometimes as the Frequentist paradigm is learned first but once you get it, it is really amazing to see the believe update in action with data.
Apr 10, 2018
I like this course a lot. Explanations are clear and much of the (unnecessarily heavyweight) maths is glossed over. I particularly liked the sections on Bayesian model selection.
por Aleix Dorca•
Mar 19, 2019
Too many formulas... More examples would be nice.
por Stefan Huber•
Mar 16, 2019
Find it hard to follow the lectures. The labs and supplement material is good though.
por Ong Yao Rui Terenze•
Mar 16, 2019
Worst course in the specialization. Totally killed my interest in statistics and R. Warning to everyone, do not do this course if you have / want to learn statistics. Only do it if you want to re-enforce the view that statistics is not something for you.
por De'Varus May•
Feb 15, 2019
Though this section in the specialization is a little more difficult than the other sections. The supplemental material provided is helpful in navigating through the course. I will continue to read through this material to further my understanding of the material.
por Toan Thien Le•
Jan 26, 2019
Good for reviewing Bayesian Statistic. But not for new learners.
The quality is below the previous courses in the same Specialization. The contents are rushed. The labs are impractical and sometimes confusing.
And beware of the final assignment. Since the number of students is low, the grading takes lots of days. And you might miss the enrollment window for the Capstone course.
por Richard Millington•
Jan 24, 2019
While the other modules so far have been terrific with good levels of support and clear explanations, this module is pretty terrible for a few reasons.
1) The level of support.
Your chances of getting a response to any question are slim - which means you're pretty much on your own here. Don't understand anything? Go find the answer elsewhere.
2) The tutors.
Mine Çetinkaya-Rundel has generally been terrific so far. Speaks slowly, repeats what variours terms mean (instead of assuming we memorize them the moment we hear them) and provides good clear examples to work from.
Sadly both Merlise and David are the opposite. They whiz through the material uncomfortably reading from a telepromter often assuming we instantly grasp every possible concept. It's almost impossible to follow most of the sessions they present. Most of the time there aren't even any exercises or opportunities to check we've understood the material correctly. They would both be 100% better if they frequently reminded us of the definitions of the concepts they use.
3) The material. There is FAR too much here to be covered in a single module. This is an entire course on its own (or a much bigger module).
4) Assumptions we know things which are never taught. I've lost track the number of times a word or concept sneaks into a quiz, into a lecture, or into an R package without explaining what it means. At times it feels this material was pulled from 2 or more sources and this has created gaps in understanding.
Sorry guys, I've really enjoyed the first three modules...but this one was a bit of a disaster.
Provide better support, shrink the material, create a better lecture experience and I'll happily revise this.
por Liew Hoe Peng•
Jan 17, 2019
This course is challenging and well-presented!
por Sara Melvin•
Dec 24, 2018
Starts out good in the first week and then ramps up to graduate level statistics without really a lot of notation explanation. Week 3 with the silver haired lady as the teacher was the WORST. nothing made sense when she taught.
por Pedro Guilherme Frade Moro•
Dec 20, 2018
por Tulio Rodrigues Carreira•
Dec 11, 2018
The last two weeks are way too hard to follow and could provide more practical examples instead of focusing on mathematical theory and formulas. That would make more sense to this course when compared to the content of the previous ones in this specialization.