ECE 313


Section X (Tue/Thu) - IYER

Fall 2014

Main Page

Course Outline

Grading Policies


Homework Problems and Solutions

Student Projects




ECE 313 (also cross-listed as MATH 362) is an undergraduate course on probability theory and statistics with applications to engineering problems primarily chosen from the areas of communications, control, signal processing, and computer engineering.

EE and CompE students must complete one of the two courses ECE 313 or Stat 410.

Credit: 3 hours.

Graduate students in the ECE Department cannot receive unit credit for ECE 313.

Prerequisite: ECE 286 or Math 415

About This Section

This section has separate homework and exams from the MWF sections (B, C, D, and E). While all sections will cover the same theoretical material, the MWF sections are the standard ECE 313, whereas this section, which is strongly recommended for computer engineering majors, will consider many examples from computer system performance, reliability, and network performance analysis, and the like. Through student projects, the class will be introduced to hands-on measurements and analysis of computer systems and networks. Analysis of the data thus gathered will introduce students to the whys and wherefores of real-life statistical problems in the reliability and performance analysis of computer systems and networks, and their solution.

Meeting time and Place: 8:00am - 9:20am Tuesday and Thursday in 3013 Electrical and Computer Engineering Building

Instructor: Professor Ravi K. Iyer

Office: 255 Coordinated Science Lab (Phone: 333-9732)


Office Hours: 12:30pm - 2:00pm, Tuesdays and Thursdays (Please contact Heidi Leerkamp )

Teaching Assistant: Homa Alemzadeh

Office: 246 Coordinated Science Lab


Office Hours: 4:00pm - 5:00pm, Mondays, in Coordinated Science Lab (CSL), Room 246
You can also submit your questions to the ECE 313 Webboard at my.ece under the topic for Section X or on Piazza.

Text: Sheldon Ross, A First Course in Probability, 9th edition, Pearson, 2012.

Further Reading and Problems: Sheldon M. Ross, Introduction to Probability Models, 10th Edition, Academic Press, 2010 (Chapters 1-5).

If you have any comments or questions about the web site, please email Homa Alemzadeh at