Many subareas of computer science and engineering are inherently empirical. Whether one is designing network routing algorithms, designing robots to navigate across harsh terrains, tuning database search parameters, or employing a machine learning algorithm to solve a robot control problem, there exist a number of common steps in the research process. These include: the proper construction of experimental questions, the design of methods to get at these questions, and the evaluation of the empirical results. In this graduate-level course, we will discuss the formulation of empirically-testable hypotheses as applied to different sub-fields of computer science, engineering, neuroscience and psychology; the design of experiments in order to test these hypotheses; and a range of statistical methods that are available for the evaluation and analysis of experimental results.
Topics will include:
Where: Felgar Hall 334
When: T/Th 1:30-2:45
Prerequisites: Statistics (Math 4743, Math 5743, Math 4753, or IE 3293) and permission of the instructor.
In order to grant permission, I am looking for research experience or an advanced course in some empirical area (for example: networks (CS 4133/5133/G5143/G6143), robotics (CS 4023/5023), operating systems (CS 4113/5113), machine learning (CS G5033), artificial intelligence (CS G4013), database management (CS G4513), computer architecture (CS G5633))
fagg cs ou.edu
Last modified: Sat Feb 5 23:57:22 2011