ECE 313/MATH 362
PROBABILITY WITH ENGINEERING APPLICATIONS
Summer 2014
EE and CompE students must complete one of the two courses ECE 313 or Stat 410.
Prerequisite : Math 286 or Math 415
Exam times : See Exam information.
This course has quizzes and a concept matrix instead of homework to be handed in. See About the Concept Matrix , Quizzes and exams , and Grading Policies for more information.
Office Hours Summary: Mondays 4-5 pm in 368 Everitt Lab, Tuesdays 3-5 pm in 168 Everitt Lab, Wednesdays 3-4 pm in 330M Everitt Lab, Thursdays 4-5 pm in 368 Everitt Lab, Fridays 3-5 pm in 168 Everitt Lab. In addition, the instructor will remain in the classroom after class to address questions on lectures, notes, or homework.
Section | Meeting time and place | Instructor |
---|---|---|
X | 12:00 -12:50 pm MTWRF 106B1 Engineering Hall |
Jiaming Xu e-mail: jxu18 AT illinois dot edu Office Hours: Available after classes; Mondays 4-5 pm in 368 Everitt Lab |
Teaching Assistants: | |||
Lili Su (netID lilisu3) | Office Hours: Tuesday 4-5 pm in 168 Everitt Lab, Thursdays 4-5 pm in 368 Everitt Lab, Fridays 3-5 pm in 168 Everitt Lab | ||
Yixiao Nie (netID nie4) | Office Hours: Tuesdays 3-5 pm in 168 Everitt Lab, Wednesdays 3-4 pm in 330M Everitt Lab, Fridays 4-5 pm in 168 Everitt Lab |
Week | Lecture Dates | Concepts (Reading)[ Short videos] | Short Answer Questions and Problems for Quizzes |
---|---|---|---|
1 | 6/16-6/20 |
*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, SAQ1.3, PokerIntro, PokerFH2P] *using Karnaugh maps for three sets (Ch 1.4)[Karnaughpuzzle, SAQ1.2] *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] |
SAQs (on p. 20) for Sections 1.2, 1.3, 1.4. Problems (pp. 21-23, 77-78) 1.2, 1.4, 1.6, 1.8, 1.10, 1.12, 2.2 (skip part about variance), 2.4. Quiz 1: 6/23 |
2.1 | 6/23-6/25 | *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] *binomial distribution (how it arises, mean, variance, mode) (Ch 2.4.3-2.4.4)[SAQ 2.4][bestofseven] |
SAQs (pp. 73-74) for Sections 2.2, 2.3, 2.4. Problems (pp. 77-82) 2.6, 2.12, 2.14, 2.16, 2.18, 2.20. Quiz 2: 6/26 |
2.2 | 6/25 - 6/27 | *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) *Poisson distribution (how it arises, mean, variance) (Ch 2.7) *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)[Simdoc-Minhash2] |
SAQs (p. 74) for Sections 2.5-2.9. Problems (pp. 82-84) 2.22, 2.24, 2.26, 2.28. If appearing on a quiz, numerical answers are not required for problems SAQ 2.5.1 or 2.7, or Problems 2.26(b) or 2.28(a). As usual, you would need to indicate how to solve the problems up to the point a calculator is needed. Quiz 3: 6/30 |
3.1 | 6/30-7/2 | *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) |
SAQs (p. 75) for Sections 2.10, 2.11. Problems (pp. 85-88) 2.30, 2.32, 2.34, 2.36, 2.38. (For 2.34 on quiz, you should realize the intervals overlap, even though you don't have a calculator.) Quiz 4: 7/3 |
3.2 | 7/2-7/3 | *union bound (Ch 2.12.1) [SAQ 2.12]
*network outage probability and distribution of capacity (Ch 2.12.2-2.12.3) *probability of undetected error for coded system (Ch 2.12.4) *cumulative distribution functions (Ch 3.1) |
SAQs (p. 75, 143) for Sections 2.12, 3.1. Problems (pp. 89-90, 145-146) 2.40, 2.42, 2.44, 3.2. Quiz 5: Monday 7/7 (in class) Exam 1: Monday, July 7 The concept matrix deadline for 3.2 is Tuesday, July 8, 5 pm as usual. |
4.1 | 7/7-7/9 | *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) |
SAQs (p. 143-144) for Sections 3.2-3.5. Problems (pp.146-148) 3.4, 3.6, 3.8, 3.10, 3.12. Quiz 6: 7/10 |
4.2 | 7/9-7/11 | *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] |
SAQs (p 144) for Section 3.6. Problems (pp. 149-150) 3.14, 3.16, 3.18. Quiz 7: Monday 7/14 |
5.1 | 7/14-7/16 | *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) *the area rule for expectation based on CDF (Ch 3.8.3) *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. 144-145) for Sections 3.7-3.10. Problems (pp. 150-155) 3.20, 3.22, 3.24, 3.26, 3.28, 3.30, 3.32, 3.36 Quiz 8: 7/17 |
5.2 | 7/16 - 7/18 | *joint CDFs (Ch 4.1)[SAQ 4.1]
*joint pmfs (Ch 4.2)[SAQ 4.2] *joint pdfs (Ch 4.3)[SAQ 4.3] *joint pdfs of independent random variables (Ch 4.4)[SAQ 4.4] | SAQs (p. 215-216) for Sections 4.1-4.4. Problems (p. 218-221) 4.2, 4.4, 4.6, 4.8, 4.10, 4.12. To shorten the problems on quizzes, Parts 4.2(c), 4.4(c), 4.6(c), 4.10(e), 4.12(d) will not be included. Quiz 9: 7/21 |
6 | 7/21-7/25 | *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] |
SAQs (pp. 216-217) for Sections 4.5, 4.6, 4.7. Problems (pp. 221-222) 4.14, 4.16. NO QUIZ 7/24 Exam 2: Thursday, July 24 Quiz 10: Monday 7/28 |
7.1 | 7/28-7/30 | *correlation and covariance (e.g. scaling properties) (Ch 4.8)[SAQ 4.8]
*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. 217) for Sections 4.8, 4.9. Problems (p. 222-225) 4.18, 4.20, 4.22, 4.24, 4.26, 4.28. (Problem 4.26 refers back to problem 4.24.) Quiz 11: 7/31 |
7.2 | 7/30-8/1 | *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.217) for Sections 4.10-4.11 Problems (pp.225-230) 4.30, 4.32, 4.34, 4.36, 4.38, 4.40, 4.42 The note in parentheses for problem 4.30 should be updated to: The problem is related to Example 4.10.5. The example is correct. Also, part (a) should refer to Proposition 4.10.1, not 4.9.1.) Quiz 12: Monday 8/4 |
8 | 8/4-8/6 | wrap up and review |
Optional Reading:
More Detailed Information
The ECE 313 FAQ |
About the Concept Matrix |
Homework |
Previous Web Pages |
Reserve Books |
Quizzes and exams |
Piazza |
COMPASS (for grades) |
Grading Policies |
Powerpoint slides |