Michael Lewis wrote:
I’m teaching a course on Bayesian statistics this fall. I’d love to use your book but think it might be too difficult for the, mainly, graduate social work, sociology, and psychology students likely to enroll. What do you think?
In response, I pointed to these two books that are more accessible than mine:
– A Student’s Guide to Bayesian Statistics.
Also, Regression and Other Stories, but that’s not really a Bayesian book, even though it has some Bayesian stuff in it.
Statistical Rethinking is what I am using in our courses and workshops for folks. I like it. Most folks are from non-stat/mathy backgrounds. I also borrow from https://lindeloev.github.io/tests-as-linear/ but use rstanarm for the examples.
+1 rethinking.
Is “Regression and Other Stories” available yet?
I wondered the same thing. Googled a bunch, and discovered that it’s one of the two volumes in the (planned?) sequel to the Gelman/Hill book. Seems like it’s not available for purchase yet.
+1
Regression and Other Stories is done. We just have to go through the publication process. I guess it will be available in a few months.
That’s great news!
Yeah! Do you have a rough date for when the web version will appear? I want to use it for a spring semester class.
D,
When I know dates, I’ll post something.
Another +1 for rethinking. It’s excellent for non-statisticians. Also, there is a great youtube series (actually, three of them) from McElreath’s teaching of the course. This would be a terrific supplement for students.
How about William Bolstad’s “Introduction to Bayesian Statistics” for a basic level?
What is the background of the intended audience? Impossible to suggest anything without that information.
I am slowly working my way through Lambert’s A Student’s Guide to Bayesian Statistics. on my own and finding it pretty good. Overall, I get the feeling that the overall math level is not too high for psychology student speaking as a former psychology grad student whose last calculus course was over 40 years ago and has no background in Bayesian statistics.
Lambert has extensive on–line resources. I have only viewed some of the videos and they seem good. Overall, with a good instructor, I think it would be a good text.
As an aside, I was reading the book while in hospital: Doctors and nurses recoiled in shock (horror?) when they saw the open book.
Lambert’s book is okay for expositional purposes, but his end-of-chapter problems are way too far afield for an early non-stats graduate student. Also, the later chapters are not nearly as well developed as the first half of the text. Lambert’s videos are, admittedly, excellent, however and the book has parts where it’s language shines through. But for practical implementation of the methods definitely look elsewhere.
I’ve liked Kruschke’s Doing Bayesian Data Analysis. Kruschke is a psychologist so it’s definitely written from a practical approach over a math approach, although there is still some math in there. It’s written mostly for JAGS but there is some RStan as well.
+2 for Kruschke. It’s well-written and great at introducing the concepts without getting too mathy.
I also agree about Kruschke’s book. It has a lovely intuitive explanation of MCMC.
If you’d like more Stan (via brms) with your Kruschke, I’ve worked through most of the book (GitHub repo: https://github.com/ASKurz/Doing-Bayesian-Data-Analysis-in-brms-and-the-tidyverse) and am slowly stitching the chapters together into an online book (https://bookdown.org/ajkurz/DBDA_recoded/). All are free make suggestions.
Another +1 for rethinking. It’s the only stats book I’ve ever read for fun. Accessible and informative for a wide variety of audiences.
Perhaps a good place to start are
(1). Statistics & Data Analysis for Financial Engineering, with R examples. 2nd Ed., David Ruppert & David S. Matterson
Chapter 20, Bayesian Data Analysis & MCMC
(2). Information Theory, Inference & Learning Algorithms, David J.C. MacKay,
Chapter 37, Bayesian Inference & Sampling
http://www.inference.org.uk/mackay/itila/
(I’ve got a small slide pack, which I’m happy to share with you. If you’re interested, just let me know).