# Creating structured and flexible models: some open problems

[This article was first published on

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Prof. Andrew Gelman, from both the Statistics and Political Science departements at Columbia presented this talk to the New York R Statistical Programming Meetup on October 7, 2010.**VCASMO - drewconway**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Description: A challenge in statistics is to construct models that are structured enough to be able to learn from data but not be so strong as to overwhelm the data. We introduce the concept of “weakly informative priors” which contain important information but less than may be available for the given problem at hand. We also discuss some related problems in developing general models for interactions. We consider how these ideas apply to problems in social science and public health. All the work for these projects was done in R.

To

**leave a comment**for the author, please follow the link and comment on their blog:**VCASMO - drewconway**.R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.