Description: Topics include approaches for evaluating, writing, and presenting scholarly papers, research integrity issues, and quantitative models and methods in experimental computer science. Techniques for the use of analytic and simulation models, design of experiments, hypothesis testing, and statistical analysis of data are presented. Students apply these techniques to a project, write a report, and make a presentation to the class.
All PhD CS students with start term Spring'23 or Fall'23 must take this course during Fall'23.
Prerequisites: Admission to PhD in Computer Science or PhD in Information Technology programs.
Course Delivery: This is a synchronous online course with weekly meetings on Monday 4:30 - 7:10 PM. The link for the online meeting will be sent to the students' GMU email addresses by the instructor.
Technology Requirements: Since this is an online course, the students should have access to a device (e.g., a laptop computer) that can access online course materials (on Blackboard), Internet with sufficient bandwidth to attend synchronous online class meetings, a webcam and a microphone to fully participate to all class activities.
Required reading:
David Lilja, Measuring Computer Performance: A Practitioner's
Guide,
Cambridge University Press, 2000.
Recommended readings:
Raj Jain, The Art of Computer Systems Performance Analysis, John
Wiley, 1991, ISBN: 0-471-50336-3.
P. Cohen, Empirical Methods for Artifical Intelligence, MIT Press,
1995.
I. Miller, J. Freund, R. Johnson, Probability and Statistics for
Engineers, Sixth Edition, Prentice Hall, 2000, ISBN: 0-13-014158-5.
Instructor Office Hours: Tuesday 2:00 - 3:00 PM and by appointment (online - See Blackboard for the link).
Graduate Teaching Assistant (GTA):
Amir Payandeh (apayande@gmu.edu)
GTA Office Hours: TBA.
Grading: Grading components will be as follows.
Students need to earn at least 90% (as the weighted overall semester score)
to be considered for A. Students with overall score less than 50% will
receive F.
No early midterm/final exams will be given and make-up
exams are strongly discouraged. A
student should present an official and verifiable excuse to miss a midterm/final exam (such
as a doctor's note).
Completed homeworks and assignments must be submitted on Blackboard, unless otherwise stated. If a student makes multiple submissions, only the last submission will be graded. It is critical that the students double check the files they are submitting, as submitting a wrong, corrupt, or empty file is very likely to result in a score of 0 for that assignment. Students are responsible for keeping back-ups of their work while they are working on an assignment. The students are required to take measures to protect the confidentiality of their class work on shared computers.
All students must abide by the GMU Honor Code and CS Department's Honor Code and Academic Integrity Policies during the semester. The students are supposed to work individually on the assignments (unless the assignment explicitly allows working in a group). The violations of Honor Code will be reported to GMU Honor Council with the recommended sanction of F in the course (at a minimum).
The students, if they feel that their work is not accurately graded, must initiate contact with the grader within seven days that follows the availability of the grade on Blackboard. Grade contesting beyond this time window will not be allowed.
Class Home Page: Throughout the term, the course material (announcements, slides, handouts, etc.) will be available on the GMU Blackboard system. Important announcements will be also sent by e-mail to the students' GMU e-mail addresses.
Disability Statement: If you have a learning or physical difference that may affect your academic work, you will need to furnish appropriate documentation to GMU Disability Resource Center (DRC). If you qualify for accommodation, the DRC staff will give you a form detailing appropriate accommodations for your instructor. If you have such a condition, you must contact the instructor during the first week of the term about the issue.