George Mason University
George Mason University Mason
George Mason University

CS 700: Quantitative Methods and Experimental Design in Computer Science

Instructor Information

Section Information

Integrated treatment of models and practices in experimental computer science. Topics include scientific methods applied to computing, workload characterization, forecasting of performance and quality metrics of systems, uses of analytic and simulation models, design of experiments, interpretation and presentation of experimental results, hypothesis testing, and statistical analyses of data. Involves one or more large-scale projects.

Course Information from University Catalog

Not Repeatable


Integrated treatment of models and practices in experimental computer science. Topics include scientific methods applied to computing, workload characterization, forecasting of performance and quality metrics of systems, uses of analytic and simulation models, design of experiments, interpretation and presentation of experimental results, hypothesis testing, and statistical analyses of data. Involves one or more large-scale projects.

Hours of Lecture or Seminar per week: 3

Credits: 3

Prerequisites:

Admission to PhD program in Computer Science or Information Technology, and at least two 600-level courses offered by the Computer Science Department.

Instructor Information
Expertise