ECE 313/MATH 362
PROBABILITY WITH ENGINEERING APPLICATIONS
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.
Prerequisite : Math 286 or Math 415
Detailed course description
Course information in course explorer
except July 4
|11am-12pm||3034 ECEB||3034 ECEB||3034 ECEB|
|3-5pm||3034 ECEB||3034 ECEB||3034 ECEB|
|6-7pm||Zoom link for this office hour||Zoom link for this office hour||Zoom link for this office hour|
|7-8pm||Zoom link for this office hour|
|8-9pm||Zoom link for this office hour|
|Section||Meeting time and place||Instructor|
1013 ECE Building
e-mail: alvarez AT illinois dot edu
Mondays, 11-11.50am, 3034 ECEB.
Wednesdays, 11-11.50am, 3034 ECEB.
Thursdays, 11-11.50am, 3034 ECEB.
|Ali Yekkehkhany (yekkehk2 AT illinois dot edu)||Office Hours:|| Mondays, 3-5pm, 3034 ECEB,
Wednesdays, 3-5pm, 3034 ECEB,
Thursdays, 3-5pm, 3034 ECEB.
|Kiwook Lee (klee137 AT illinois dot edu)||Office Hours:||via Zoom, Monday 6-8pm, Tuesday-Wednesday, 7-8pm.|
|Amr Martini (ammartn3 AT illinois dot edu)||Office Hours:||via Zoom, Tuesday-Wednesday 6-7pm, Thursday 6-8pm.|
|Shiyi Yang (yang158 AT illinois dot edu)||Office Hours:||via Zoom, Monday-Thursday, 8-9pm.|
Office hours for online students will be done using Zoom. Make sure you create an account and get familiar with it.
|Concepts (Notes sections)[Short videos]|
* How to specify a set of outcomes, events, and probabilities for a given experiment (Ch 1.2)
* set theory (e.g. de Morgan's law, Karnaugh maps for two sets) (Ch 1.2)
* using principles of counting and over counting; binomial coefficients (Ch 1.3-1.4) [ILLINI, SAQ 1.3, SAQ 1.4, PokerIntro, PokerFH2P]
* using Karnaugh maps for three sets (Ch 1.4)[Karnaughpuzzle, SAQ1.2]
* random variables and probability mass functions (Ch 2.1) [pmfmean]
* mean of a function of a random variable (LOTUS) (Ch 2.2) [pmfmean]
* scaling of expectation, variance, and standard deviation (Ch 2.2) [SAQ 2.2]
* conditional probability (Ch 2.3) [team selection][SAQ 2.3]
* independence of events (Ch 2.4.1)[SimdocIntro][Simdoc-Minhash1]
|3||Thursday, June 27||
* independence of random variables and Bernoulli distribution (Ch 2.4.2-2.4.3)
* binomial distribution (how it arises, mean, variance, mode) (Ch 2.4.3-2.4.4) [SAQ 2.4][bestofseven]
* geometric distribution (how it arises, mean, variance, memoryless property) (Ch. 2.5)[SAQ 2.5]
* Bernoulli process (definition, connection to binomial and geometric distributions) (Ch 2.6)[SAQ 2.6]
* Poisson distribution (how it arises, mean, variance) (Ch 2.7)[SAQ 2.7]
Exam 1: Wednesday, June 26. Main exam: 10-10.50am, conflict exam (only available for online students): 8-8.50pm.
* Maximum likelihood parameter estimation (definition, how to calculate for continuous and discrete parameters) (Ch 2.8)
* Markov and Chebychev inequalities (Ch 2.9)
* confidence intervals (definitions, meaning of confidence level) (Ch 2.9)[SAQ 2.9,Simdoc-Minhash2]
* law of total probability (Ch 2.10) [deuce] [SAQ 2.10]
* Bayes formula (Ch. 2.10)
* Hypothesis testing -- probability of false alarm and probability of miss (Ch. 2.11)
* ML decision rule and likelihood ratio tests (Ch 2.11) [SAQ 2.11]
* MAP decision rules (Ch 2.11)
* union bound (Ch 2.12.1) [SAQ 2.12]
* network outage probability, distribution of capacity and more applications of the union bound (Ch 2.12.2-2.12.4)
NO lecture on Thursday, July 4.
Exam 2: Wednesday, July 10. Main exam: 10-10.50am, conflict exam (only available for online students): 8-8.50pm.
* cumulative distribution functions (Ch 3.1)[SAQ 3.1]
* probability density functions (Ch 3.2) [SAQ 3.2][simplepdf]
* uniform distribution (Ch 3.3) [SAQ 3.3]
* exponential distribution (Ch 3.4) [SAQ 3.4]
* Poisson processes (Ch 3.5) [SAQ 3.5]
* Erlang distribution (Ch 3.5.3)
* scaling rule for pdfs (Ch. 3.6.1)[SAQ 3.6]
* Gaussian (normal) distribution (e.g. using Q and Phi functions) (Ch. 3.6.2) [SAQ 3.6] [matlab help including Qfunction.m]
* the central limit theorem and Gaussian approximation (Ch. 3.6.3) [SAQ 3.6]
* ML parameter estimation for continuous type random variables (Ch. 3.7)[SAQ 3.7]
* the distribution of a function of a random variable (Ch 3.8.1)[SAQ 3.8]
* generating random variables with a specified distribution (Ch 3.8.2)
* failure rate functions (Ch 3.9)[SAQ 3.9]
* binary hypothesis testing for continuous type random variables (Ch 3.10) [SAQ 3.10]
* joint CDFs (Ch 4.1)[SAQ 4.1]
* joint pmfs (Ch 4.2)[SAQ 4.2]
* joint pdfs (Ch 4.3)[SAQ 4.3]
Exam 3: Wednesday, July 24. Main exam: 10-10.50am, conflict exam (only available for online students): 8-8.50pm.
* joint pdfs of independent random variables (Ch 4.4)[SAQ 4.4]
* distribution of sums of random variables (Ch 4.5)[SAQ 4.5]
* more problems involving joint densities (Ch 4.6)[SAQ 4.6.]
- Skip Section 4.7.
* correlation and covariance (e.g. scaling properties) (Ch 4.8)[SAQ 4.8]
* minimum mean square error linear estimator (Ch 4.9.3)[SAQ 4.9]
* minimum mean square error unconstrained estimators (Ch 4.9.2)
Exams will be open book.
Exams for online students will be proctored using Zoom. Make sure you create an account and get familiar with it.
You can find copies of old midterm exams and final exams here. The exams this semester might not be similar in nature as in recent past semesters because of them being open book.
The topics covered in Exam 1 are exactly the ones in the course notes up until (and including) section 2.5, except for Section 1.5.
The topics covered in Exam 2 are exactly the ones in the course notes up until (and including) section 2.12, except for Sections 1.5 and 2.9, with emphasis on Chapter 2. You should know the meanings, forms, means, and variances for the key discrete distributions.
The topics covered Exam 3 are exactly the ones in the course notes up until (and including) section 3.10, except for Sections 1.5, 2.9, and 3.9, with emphasis on Chapter 3. You should know the meanings, forms, means, and variances for the key discrete and continuous distributions.
The final exam will cover the topics in the notes through Section 4.9.3, except for Sections 1.5, 2.9, 3.9, and 4.7, with emphasis on Chapter 4. You should know the meanings, forms, means, and variances for the key discrete and continuous distributions..
If you miss a midterm exam, the following procedures apply: To receive an excused absence, you must either arrange your absence in advance with your instructor (i.e., prior to the absence), or complete an Excused Absence Form at the Undergraduate College Office, Room 207 Engineering Hall, indicating that you missed the midterm exam and the reason for the absence. This form must be signed by a physician or medical official for a medical excuse, or by the Office of the Dean of Students (Emergency Dean, 610 E. John Street, 3330050) for a personal excuse due to personal illness, family emergencies, or other uncontrollable circumstances. Present the completed form in person to your section instructor as soon as possible after you return. Scores on midterms due to excused absences will not be made up. Your midterm score for an excused absence will be the weighted average of the other midterm score and final exam score. An unexcused absence from a midterm will be counted as a 0.
If when you receive your graded midterm exam, and after looking at the posted solutions, you feel there was an inaccuracy in the grading of your exam, fill out an exam regrade request form and staple it to your exam BUT do not write on or alter in any way your original exam paper. Turn in such regrade requests to your instructor by the end of the third lecture after the graded exam is handed back.
If for some reason of emergency such as severe illness you are not able to take the final exam at the required time, you will need to obtain a written excuse from the Office of the Dean of Students.
Link to MasterProbo.FAQs:
Desktops and Laptops
Mobile (not recommended)
Lectures will be recorded daily and displayed at https://echo360.org.
You can access this site by entering your University of Illinois email address. They’ll you will be prompted to authenticate using your Active Directory (AD) password. Once you’re authenticated, you should see a dashboard page displaying content for which you are enrolled as a student.
Further documentation on how to use the Echo360 platform can be found at https://it.engineering.illinois.edu/user-guides/student-guide-echo-360