Bayesian statistics with R

Language: English (with strong French accent)

Program:
00:00 An introduction to Bayesian inference
55:19 The likelihood
1:44:40 Bayesian analyses by hand
2:17:21 A detour to explore priors
4:08:27 Markov chains Monte Carlo methods (MCMC)
5:40:05 Bayesian analyses in R with the Jags software
8:02:27 Contrast scientific hypotheses with model selection
8:19:43 Heterogeneity and multilevel models (aka mixed models)

Learning objectives:
+ Try and demystify Bayesian statistics, and MCMC methods
+ Make the difference between Bayesian and Frequentist analyses
+ Understand the Methods section of a paper that does Bayesian stuff

+ Run Bayesian analyses with R (in Jags)

[abuduasoman]

Very educative, beyond normal classroom lectures. Thanks for sharing

[danielmorenofernandez]

this video si so great. Thanks for uploading. It helped me a lot to understand the bayesian models.

again, thank you!

[niceday]

Thank you so much for opening the classroom gate.

[manuclaessens]

Thanks for sharing, it will be a great complement to my university course on Bayesian statistics, cheers!

[haniehramezaniansani]

Thanks for sharing, this course helps me to understand bayesian statistics well.

[Viperophus]

Very helpful. Thank you for sharing. Hoping to apply these methods to my work. Cheers, Chris

[bitbybit]

Thank you for sharing. Saw this on twitter.

[Rainstorm]

Thanks much sir. Its like you use the concept of prior information for interchangeably for both the parameters (beta), and the observed data (observed y values). Is that correct?

[hesbornomwandho]

thank you for sharing.found it in twitter

[mylifeisinhishandsamen]

Hi, I don't know anything about bayesian statistics but need to learn hierachical bayes. I would like to ask if this lecture also include hierachical bayes?