CS 303 is a
graduate course that examines
experimental design in computer science research. Papers often succeed
or fail based on their evaluation section. The goal of CS 303 is to
help you improve how you design experiments to evaluate your research.
It will do so by teaching you how to
through the strengths and limitations of
an experimental design
- Design new
experiments to unambiguously measure
which experiments to include, given
The class will also teach basic uses of R for data analysis. Note
to participants: please take a few minutes prior to the first class to download R.
will have two major parts. The first is
a series of experimental case studies from human-computer interaction,
natural language processing, and computer systems. These case studies
will include examples of exemplary depth, standard practices,
innovative designs, and unforeseen flaws. The second major part of the
course is a project, where students design and execute experiments for
either their own research or prior work. Members of the class will
constructively critique and discuss each other's designs. Coursework
for the class involves problem sets in R that recreate experimental
results in papers as well as a final project.
The course is
paper-centric and has no textbook.
Participants will be expected to keep a "lab notebook" in the form of a
blog (please see Blogger).
control will be handled using Git.