For the Data Science Seminar, Wed 25 Oct, 3:30pm in Physics and Astronomy Auditorium – A102:

The Statistical Crisis in Science

Top journals routinely publish ridiculous, scientifically implausible claims, justified based on “p < 0.05.” And this in turn calls into question all sorts of more plausible, but not necessarily true, claims, that are supported by this same sort of evidence. To put it another way: we can all laugh at studies of ESP, or ovulation and voting, but what about MRI studies of political attitudes, or stereotype threat, or, for that matter, the latest potential cancer cure? If we can’t trust p-values, does experimental science involving human variation just have to start over? And what to we do in fields such as political science and economics, where preregistered replication can be difficult or impossible? Can Bayesian inference supply a solution? Maybe. These are not easy problems, but they’re important problems.

For the Department of Biostatistics, Thurs 26 Oct, 3:30pm in Room T-639

Health Sciences:

Bayesian Workflow

Bayesian inference is typically explained in terms of fitting a particular model to a particular dataset. But this sort of model fitting is only a small part of real-world data analysis. In this talk we consider several aspects of workflow that have not been well served by traditional Bayesian theory, including scaling of parameters, weakly informative priors, predictive model evaluation, variable selection, model averaging, checking of approximate algorithms, and frequency evaluations of Bayesian inferences. We discuss the application of these ideas in various applications in social science and public health.

**P.S.** It appears I’ll have some time available on Wed morning so if anyone has anything they want to discuss, just stop by; I’ll be at the eScience Institute on the 6th floor of the Physics/Astronomy Tower.

Do you suppose webcasts will be available? That would be neat.

I will be coming to the Wednesday talk and I’m excited to get to meet you. I also have what I think is a new approach to variable reduction I would be interested in getting outside perspective on. When you say Wednesday morning, approximately what hours do you think?

Eric,

Starting 9 or 10am, I guess.

I’d love to take a look at the slides if those are available, thanks!

Colin:

The first talk had no slides. Slides for the second talk are here.

As a newcomer to bayesian modeling, I too would be interested in the slides/webcast. Especially for the Bayesian Workflow talk.

James