Introduction to Bayesian data analysis - part 3: How to do Bayes?

Try my new interactive online course "Fundamentals of Bayesian Data Analysis in R" over at DataCamp: www.datacamp.com/courses/fund...
----
This is part three of a three part introduction to Bayesian data analysis. This last part aims to gives some pointers to how Bayesian data analysis can be done in practice. If you haven't watch part one and part two, I really recommend that you do that first: • Introduction to Bayesi...
Links from the video:
How to install Stan: mc-stan.org/interfaces/
Stan cheat sheet: goo.gl/BmvSqM
R exercise: goo.gl/cuKzpD
Python exercise: goo.gl/Nm6naZ
Bonus Exercise: goo.gl/hRDAIE

[@saurabhkhodake]

The best bayesian video out there.... i hope youtube picks up my keywords and put this video right at top of search results

[@rasmusab]

Thanks Saurabh! :D

[@michaelrobertson9517]

This series is a _pedagogical masterpiece_. Thank you!!

[@matrixtoogood5601]

The best series on Bayesian Data Analysis I could find on the internet!

[@clivebird5729]

Ramus, a sincere thank you for your 3 part Bayesian data analysis. So well introduced, I've signed up to DataCamp and enrolled on your, 'Fundamentals on Bayesian data analysis in R'. Awesome. Thanks.

[@callummatchett8937]

Exceptional 3 part series on probabilistic modelling. I keep coming back to these videos for a refresher

[@gueyenono]

You are a phenomenal teacher. Thank you for the tutorials.

[@sambennett9901]

This is an incredible tutorial series! You take something that could be quite complicated for a beginner and explain it so well, thank you!

[@ishaaittoo9293]

A theory historically emphasized by Fisher and a Fish example.
Damn you're good. THANK YOU SO MUCH

[@Jaaksonajalg]

A really good overview, thanks! The fish graphics, Hokusai sketches and presenting the problem as a case of Catch-22 made your tutorial particularly enjoyable.

[@focker0000]

you have a very deep comprehension of Bayesian theory and i appreciate of all your videos!!

[@ShivaramakrishnaReddy]

This really helped me understand the process of this! Thank you so much!

[@DanielBurrueco]

Very good introduction to Bayesian analysis, thank you!

[@meqhas09]

Thank you Rasmus, these three parts are hilarious, especially with their fantastic and informative exercises. I really enjoyed them. Thank you again.

[@kubawlo]

Thank you for this series of videos. Very clear explanation with first building intuition and then wrapping it with some minimal maths behind it. The best way of explaining the universe.

[@hainingzhou9876]

Thank you very much! the ideas and the tools introduced in this video is suuuuuuuuper helpful for my research.

[@AnnaB-oo5bd]

Congratulations on designing and delivering a great tutorial! Brilliant

[@juliocardenas4485]

You rock sir !!
This is the best explanation I have ever seen. Thank you for helping to take my skills to the next level

[@TheScepticalinquirer]

Awesome job!!! Beautifully built and presented...

[@araplagat_]

my first time taking a peek at Bayesian data analysis, and its been a good start, although it took me hours to grasp a little. Thank YOU,

[@omidgeysar7680]

Thank you so much, one of the best presentation I have ever seen!

[@mathom21]

Outstanding material (all parts). Many Many Thanks!!!

[@MrOfferm]

Thank you very much for posing this!

[@jasonthomas2908]

This series has been very helpful. Thanks for that.

[@kristiapamungkas697]

Amazing introduction! I have just enrolled in your course via Datacamp

[@jadhinawi7409]

Great intro with a very smooth presenting skills. Many thanks Rasums!

[@sonigirjesh]

Awesome !! Simple and practical. Thanks.

[@kurtludikovsky1654]

Excellent Introduction.
Thanks a lot!

[@jobyjoy636]

This is Brilliant ! Thank you so much.

[@user-qc9qp9qp5e]

a really really nice tutorial for Bayesian beginner!!!

[@ankushkothiyal5372]

Thank you for these tutorials.

[@aleksandermolak5885]

Thank you Rasmus! Great playlist!

[@vatsaakhil]

Thank you so much for this series, I'm starting the Kruschke puppy book soon!

[@yusufibrahim1005]

Thank for making good introduction on bayesian data analysis its rely helpful

[@leledavid]

thanks for making these videos, very useful!

[@niklase5901]

Great video Rasmus!

[@NathalieTamayo]

Excellent explanation, thanks

[@12copablo]

Thx so much for these videos! Really helped!

[@syrphus]

Thank you for making these videos!

[@georgekochuparampil4238]

Excellent Presentation, congratulation Rasmus

[@albertomedinarobredo]

you are very good!! See you in your data camp course!

[@larsrichter9978]

Amazing job!

[@clezcanopy]

excelent tutorial, very appreciate it

[@laurentcapolungo2261]

Rasmus, fantastic lectures. I watch them late at night and can learn immensely while putting my newborn to sleep (my son is getting used to your voice )

[@pedrobatista5724]

this is great, thanks!!

[@sakkariyaibrahim2650]

Great lecture

[@Leoooooo976]

You are indeed amazing!

[@thomaslees1892]

Thank you so much this tutorial was awesome! A massive help

[@leonkk2712]

great job

[@RV-oo6dh]

Well done! Thank you for these videos Rasmus - you've presented the subject fantastically well. I wonder how long did it take you to put this together...?

[@bombaikos]

Bravo!

[@piotralanp]

28:57 - the funniest waiting song ever, turn on the subtitles.
"do pootaroo to tentacle creature
chica - chicken chicken coop -
- you could do the chicken but...
do-do-do-do"
LOL

[@rasmusab]

My good!!! Tears in my eyes! :D So I guess the auto-translate subtitles doesn't like my singing :D

[@RohitKalia]

Due to your comment i watched the video again. It's hilarious

[@farnazbayaat5955]

amazing

[@xiaoqingzhang9556]

You are so cool!

[@sovitgurung4062]

Thanks alot

[@user-or7ji5hv8y]

Have you tried Pyro? Which package do you recommend? I understand that PyMC3 has a large community.

[@Ivan-td7kb]

Wait so if we use MCMC to walk around the parameter space why do we even need the prior distribution? Is it only used to initialize the starting value of the MCMC?

[@jiachen1078]

thanks so much. but can you explain how metropolis hastings works? :D

[@jameswilliamson1726]

My Stan program in Python can create the correct model, but doesn't finish a fit in hours... not even with iter = 10. Any ideas?

[@edgardesouzavismara7798]

Quite nice videos! How did you create those fine graphs of likelyhood!

[@rasmusab]

Everything is made in scratch from R with a lot of pretty ugly code :)

[@edgardesouzavismara7798]

:) Could you share the code? I never saw the likelihood surface represented in the way.

[@joeya6635]

I hate R,is it possible to do all these just in python?

[@citiblocsMaster]

36:29 "by me in a amazon review". Love it. Edit: that comment is featured on the book homepage: xcelab.net/rm/statistical-rethinking/. You were not kidding

[@TheChibisu]

I love hairy caterpillars now!!

[@moroccotech7750]

what about using some application on information security

[@walter_ullon]

The lack of likes here is pretty criminal....