The substance of this course will consist of research on two topics, moral judgment and prediction. There will be a few exercises that everyone does, and projects, which may be done in groups. There will also be some reading, but I have not figured out yet what that will be.
In moral judgment, the main topic of interest is the determinants of utilitarian vs. deontological judgments, that is, roughly, judgments based on consequences or based on moral rules. A major theory here is the dual-system approach of Joshua Greene.
Relevant reading:
Baron/Ritov
Prediction of future events is related to judgment more generally, when there is a right answer. The abilities involved in prediction overlap with those involved in getting the right answer, and expressing appropriate confidence, to difficult questions. I am involved in a large project, directed by Prof. Barbara Mellers and Prof. Philip Tetlock, to explore the factors that make for good and bad predictions.
The methods will involve the use of R, "a language and environment for data analysis and graphics". R can run on all platforms, and it is free, so you can use it on their own computers, and continue to use it after you leave Penn. There is a local help list. Students will join that list and help each other. Of course I will help too. R is now the main platform for development of new statistical tools. It is also a good way to learn about command-line applications, scripts, and various programming concepts (functions, data types, etc.).
R general references:
Introduction: the authoritative source to read first
Quick R: good reference
Some hints for the beginner
Baron/Li notes
Platform-specific issues:
MacOSX-FAQ
Windows-FAQ
Introduction for Windows users
ESS (Emacs Speaks Statistics) - all platforms
Tinn-R: A recommended editor for Windows (if you can't deal with Emacs plus ESS)
Tinn-R book
Reference cards:
My reference card
Tom Short's reference card
William Revelle's reference card
Substantive statistics:
Verzani's Simple R
Revelle's R guide
Revelle's book (advanced)
A
more basic introduction to reliability (section 2)
Writing reports:
How to write
a research report in psychology
Some of the projects and exercises will be done on the class itself. But one of the substantive topics of interest is how to study individual differences, and that requires something on the order of 100 subjects per experiment. I have funding (especially from the prediction project) to pay external subjects.