## ECE 313

## PROBABILITY WITH ENGINEERING APPLICATIONS

## Section F (Mon/Wed) - IYER

## Fall 2016

## Home

#### 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 210

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### About This Section

#### This section has separate homework and exams from the other sections (A, B, C, D and E). While all sections will cover the same theoretical material, the sections A, B, C, D and E 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: 11:00 - 12:20 Monday and Wednesday in 1109 Siebel Center for Computer Science

Instructor: Professor Ravi K. Iyer

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

Email: rkiyer@illinois.edu

Office Hours: Mondays and Wednesdays, 12.30 - 2.00 PM in room CSL 255

Teaching Assistant: Yogatheesan Varatharajah

Office: 249 Coordinated Science Lab

Email: varatha2@illinois.edu

Office Hours: Tuesdays and Thursdays, 2.00 - 3.00 PM, in room CSL 249

#### Text: Sheldon Ross, A First Course in Probability, 9th edition, Pearson, 2012. (8th edition is available online for free download)

Additional reading: ECE 313 Course Notes by Prof. Bruce Hajek

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 the TA at varatha2@illinois.edu.

**Piazza will be used for course related discussions.**

**Grades will be posted in Compass.**