ECE ILLINOIS

ECE 313
Section X (Tue/Thu)

Course Outline (Tentative)

Main Page

Course Outline

Grading Policies

Lectures

Homework Problems and Solutions

Student Projects

Resources

Exams

Piazza

Date

Concepts

Notes

Homework

In-class Activity

Mini Projects + Final Project

Aug. 26

Probability Theory Basic

Lecture 1

 

 

 

 

Aug. 28

Algebra of Events
Probability Axioms
Steps to problem solving
Combinatorial Problems

Lecture 2

HW 1

 

 

Sep. 2

 

Conditional probability
Bayes formula
Total probability

Lecture 3

 

 

 

Sep. 4

Independence and mutual exclusivity
Mini project 1 description

Lecture 4

HW 2
(Not graded)

 

 

Mini Project 1 Posted

Sep. 9

 

Reliability evaluation applications

  1. Series systems
  2. Parallel redundancy

Lecture 5

 

 

Group Activity 1

 

Sep 11
  1. Series-parallel system evaluation
  2. Non-series-parallel systems

Bernoulli Trials
Triple Modular Redundancy (TMR)

Lecture 6

 

HW 3

 

Mini Project 1 Due

Sep. 16

More Reliability Application Examples

Lecture 7

 

Group Activity 2

 

Sep. 18

Introduction to random variables
Discrete and Continuous Random variables
Probability Mass Functions (PMF)

Lecture 8

HW 4

  

 

Sep. 23

Cumulative distribution function (CDF)
Discrete Random Variables

  1. Probability mass function
  2. Important discrete random variables:
  • Bernoulli and Binomial Distributions

Continuous random variables
Intro to probability density function (PDF)

Lecture 9

 

 

 

Sep. 25

  • Poisson Distribution
  • Geometric & Modified Geometric Distr.

Lecture 10

HW 5

 

 

Sep. 30

 

 Continuous random variables
  1. Probability density function (PDF)
  2. Important continuous random variables
  • Gaussian (Normal) Distribution

Lecture 11

 

Group Activity 3

 

Oct. 2
  • Gaussian (Normal) Distribution

Mini Project 2 description

Lecture 12

HW 6
(Not graded)

 

Mini Project 2 Posted

Oct. 7

Exponential Distribution

  • Gaussian (Normal) Distribution
  • Exponential Distribution
  • Memory-less property
  • Relationship to Poisson distribution

Lecture 13

 

 

 

Oct. 9
  • Hypo-exponentials
  • K-stage Erlang
  • Gamma
  • Hyper-exponential
  • Applications to reliability evaluation

Lecture 14
Video

HW 7
(Not graded)

 

Mini Project 2 Due

Oct. 14

 

Midterm Review

Lecture 15

 

 

 

 

Oct. 16

Midterm Exam – 8:00 AM

Midterm Exam

HW 8

 

 

Oct. 21

 

Expectations
Moments: Mean and variance
Mean/variance of important random variables
Functions of random variables

Lecture 16

 

 

 

 

Oct. 23

Reliability evaluation applications:

  • Mean time to failure
  • Failure rates
  • Hazard functions

Lecture 17

HW 9

 

Oct. 28

 

 

Reliability evaluation applications:

  • Intoduction to Treatment of Failure Data

Lecture 18

 

 

 

Group Activity 4

 

Oct. 30

 Review:

  • Poisson and Exponential Distributions
  • Reliability and Hazard Functions
Treatment of Failure Data

Lecture 19

HW 10

 

 

Nov. 4

Joint Distribution Functions
Conditional Distributions
Independence of Random Variables
Covariance and Correlation

Lecture 20

 

Nov. 6

Binary Hypothesis Testing

  • Basics
  • Maximum likelihood (ML)
  • Maximum A-Posteriori Probability (MAP)
  • Likelihood Ratio Test (LRT)

Lecture 21

HW 11

   Final Project posted  

Nov. 11

 

Final Project Overview

Lecture 22

 

Group Activity 5  

Nov. 13

Inequalities and Limit Theorems
Markov Inequality
Chebyshev’s inequality Law of large numbers
The Central Limit Theorem

Lecture 23

 

 

 

Nov. 18

 

Lecture 24

 

 

Group Activity 6

 

Nov. 20

First project presentations

 

HW 12

 

First project presentation 

Nov. 25

 

Nov. 27

 

Thanksgiving Break

 

 

 

 

 

Final project progress report

Dec. 2

Review Problems

Lecture 25

 

Group Activity 7

 

Dec. 4

Final Exam Review

Lecture 26

 

 

 

Dec. 5

Final Project Presentations - 6:00 - 9:00 PM

 

 

 

 

Dec. 9

Final exam review

Lecture 27

 

 

 

Dec. 12

Final Exam – 8:00 AM