I'm a computer scientist working in data mining. It's no secret to say that computer scientists are fairly poor at doing systematic experimental design and evaluation - the use of p-values and confidence estimates is considered advanced :).
What I'd like to know if there are good courses/material to teach computer scientists about good experimental design. To make this more specific, I'll add the following information:
- The course should be targeted at graduate students who can be assumed to have a reasonable understanding of probability, but limited background in statistics.
- The course should focus on experimental design in "uncontrolled unnatural settings": in other words there is neither an underlying physical ground truth or a way to control the data gathering process (as with human subjects). Of course a good course will focus on fundamentals, but it should deal with this scenario in a significant way.
- A computational element would be a bonus but is not mandatory. We deal with lots of data, but can figure out computational issues ourselves if need be.