This is a talk I gave this week in Advanced Biostatistics at McGill. The goal was to provide an gentle introduction to Bayesian methodology and to demonstrate how it is used for inference and prediction. There is a link to an accompanying R script in the slides.

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Nice set of intro. slides. Just one comment: that’s “the likelihood principle”.

Oh goodness, that’s embarrassing. Indeed, it should read ‘Likelihood principle’, not ‘Likelihood principal’. While some may consider likelihood to be of primary importance (principal) to statistical inference, the slide refers to the rule as formulated by Fisher (ie. the principle.)

Cheers.

Nice presentation. I failed to get the R source and slides files. The bit/ly links pointed to mcgill.ca site, however the server returned errors. I will appreciate of you could make these two files available. Thanks

Ouch, ya, that’s a dead link. I have put he script up here: https://github.com/cjbayesian/Bayesian-Intro-Workshop

Thanks very much.

BTW, the links to this page in the README.md file at https://github.com/cjbayesian/Bayesian-Intro-Workshop is not complete.