Section	Meeting time and place	Instructor
E	9 MWF 3015 ECE Building	Professor Naresh Shanbhag e-mail: shanbhag illinois dot edu Office Hours: Mondays 10-11am, ECEB 3034.
C	10 MWF 3017 ECE Building	Professor Bruce Hajek e-mail: b-hajek AT illinois dot edu Office Hours: Fridays 1-2pm, ECEB 4034.
D	11 MWF 3017 ECE Building	Professor Juan Alvarez e-mail: alvarez AT illinois dot edu Office Hours: Thursdays, 2-3pm, ECEB 3034. figures and notes
F	1 MWF 3017 ECE Building	Professor Pramod Viswanath e-mail: pramodv AT illinois dot edu Office Hours: Fridays, 2-3pm, ECEB 4034.
B	2 MWF 3015 ECE Building	Professor Yi Lu e-mail: yilu4 AT illinois dot edu Office Hours: Fridays, 3-4pm, ECEB 4034.

Graduate Teaching Assistants

Maojing Fu mfu2 AT illinois dot edu	Office Hours: M 4-5pm, T 3-7pm, Th 3-5pm.
Ali Yekkehkhany yekkehk2 AT illinois dot edu	Office Hours: M 2-4pm, T 1-4pm, W 1-4pm.
Cheng Chen cchen130 AT illinois dot edu	Office Hours: M 2-3pm, T 2-5pm.
Fardad Raisali raisali2 AT illinois dot edu	Office Hours: M 3-6pm, T 1-3pm and 4-7pm.
Weihao Gao wgao9 AT illinois dot edu	Office Hours: M 5-6pm, T 5-7pm, F 4-5pm.

Concept constellation

Concept matrix

Course schedule (subject to change)
Quiz # Quiz date	Lecture dates	Concepts (Reading)[ Short videos]	Short Answer Questions (SAQ) and Problems for Quizzes
1 Mon, 2/1	1/20-1/29	* 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]	SAQs (on p. 20) for Sections 1.2, 1.3, 1.4. Problems (pp. 21-24) 1.2, 1.4, 1.6, 1.8, 1.10, 1.12. Optional: [SAQ 1.5]
2 Mon, 2/7	2/1-2/5	* random variables, probability mass functions, and mean of a function of a random variable (LOTUS) (Ch 2.1, first two pages of 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 and random variables (Ch 2.4.1-2.4.2) [SimdocIntro] [Simdoc-Minhash1]	SAQs (pp. 74-75) for Sections 2.2 & 2.3 Problems (pp. 77-82) 2.2 (quiz won't ask for mean and variance), 2.4, 2.6 (quiz skips parts (d) & (e)) , 2.12, 2.14, 2.16.
3 Mon, 2/15	2/8-2/12	* 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]	SAQs (p. 75) for Section 2.4-2.7. Problems (pp. 83-85) 2.18, 2.20, 2.22, 2.24. For problems asking for a numerical answer, on a quiz you would only need to indicate how to solve the problems up to the point a calculator is needed.
4 Mon, 2/22	2/15-2/19	* Maximum likelihood parameter estimation (definition, how to calculate for continuous and discrete parameters) (Ch 2.8) [SAQ 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)	SAQs (pp. 75-76) for Sections 2.8-2.10 Problems (pp. 85-88) 2.26, 2.28, 2.30, 2.32, 2.34
5 Mon, 2/29	2/22-2/26	* 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 and its application (Ch 2.12.1) [SAQ 2.12] * network outage probability and distribution of capacity, and more applications of the union bound (Ch 2.12.2-2.12.4)	SAQs (p. 76) for Sections 2.11 & 2.12 Problems (pp. 88-93) 2.36, 2.38, 2.40, 2.42, 2.44, 2.46 (For 2.38 on quiz, you should realize the intervals overlap, even though you don't have a calculator.) Exam 1: Wednesday, March 2, 7-8.15pm
6 Mon, 3/7	2/29-3/4	* 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]	SAQs (p. 145-146) for Sections 3.1-3.4. Problems (pp.148-150) 3.2, 3.4, 3.6, 3.8, 3.10.
7 Mon, 3/14 No Lecture 3/11, EOH	3/7-3/9	* 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]	SAQs (p 146) for Sections 3.5 & 3.6 (#1-3). Problems (pp. 151-152) 3.12, 3.14, 3.16.
8 Mon, 3/28	3/14-3/18	* 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]	SAQs (pp. 146-147) for Sections 3.6 (#4)-3.10. Problems (pp. 152-156) 3.18, 3.20, 3.22, 3.24, 3.26, 3.28, 3.30, 3.32, 3.34, 3.38.
	3/21-3/25	Spring	vacation
9 Mon, 4/4	3/28-4/1	* joint CDFs (Ch 4.1) [SAQ 4.1] * joint pmfs (Ch 4.2) [SAQ 4.2] * joint pdfs (Ch 4.3) [SAQ 4.3]	SAQs (pp. 220-221) for Sections 4.1-4.3. Problems (pp. 155-156) 4.2, 4.6. To shorten the problems on quizzes, Parts 4.2(c,d), 4.6(c) will not be included.
10 Mon, 4/18 (skip 4/11)	4/4-4/15	* 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] * joint pdfs of functions of random variables (Ch 4.7) [SAQ 4.7] (Section 4.7.2 and 4.7.3 will not be tested for concept certification nor in the exams)	SAQs (p. 221) for Sections 4.4-4.6 (not 4.7). Problems (p. 223-227) 4.4, 4.8, 4.10, 4.12, 4.14, 4.16. To shorten the problems on quizzes, Parts 4.4(c), 4.10(e), and 4.12(d) will not be included. Exam 2: Wednesday, April 13, 7-8.15pm (no quiz April 11, the matrix certification deadline for this quiz is Tuesday, April 19)
11 Mon, 4/25	4/18-4/22	* correlation and covariance: scaling properties and covariances of sums (Ch 4.8) [SAQ 4.8] * sample mean and variance of a data set, unbiased estimators (Ch 4.8, Example 4.8.7) * minimum mean square error unconstrained estimators (Ch 4.9.2) * minimum mean square error linear estimator (Ch 4.9.3) [SAQ 4.9]	SAQs (p. 222) for Sections 4.8-4.9. Problems (p. 227-230) 4.18, 4.20, 4.22, 4.24, 4.26, 4.28.
12 Mon, 5/2	4/25-4/29	* law of large numbers (Ch 4.10.1) * central limit theorem (Ch 4.10.2) [SAQ 4.10] * joint Gaussian distribution (Ch 4.11) (e.g. five dimensional characterizations) [SAQ 4.11]	SAQs (p.222) for Sections 4.10-4.11 Problems (pp.230-235) 4.30, 4.32, 4.34, 4.36, 4.38, 4.40, 4.42.
-	5/2-5/4	wrap up and review

Optional Reading:

• D. V. Sarwate, Probability with Engineering Applications, Powerpoint Slides for ECE 313, Fall 2000