EE
322 (STAT 322): Probabilistic Methods for Electrical Engineers
(webpage has been re-organized)
- Updates/Reminders
- Make Up Exam and its Solution posted in the
Quizzes/Exams section.
- Need not
do problem 38 of HW 10
- Handouts and
readings forChapter 4 and for hypothesis testing posted in Handouts
section
- Quiz
8 solution posted next to the Quiz.
- HW
9 & 10 solutions will be emailed to you on Thursday.
- HW
10 posted, due date postponed to Thursday, Nov 30
- Make-up Midterm on December 7
(Thursday)
- Final Exam on December 12
(Tuesday)
- QUIZ 8(posted in the
Quizzes section):
Take home quiz, due Fri Nov 17 in my office before 5pm
- All review
sessions replaced by group office hour 4-6pm on Tuesday.
- NEW: Links to calculus
handouts (and other info on the web) posted: PLEASE revise
- Next handout posted
- Link to MIT course page and
link to Textbook errata posted in the Handouts section
- Class time:
Tuesday-Thursday 11:00-12:15
- Location: PHYSICS 0003
- Instructor: Dr Namrata Vaswani
- Office Hours:
Tuesdays 2-3pm, Fridays 2-3pm or email/call to fix a time
- Email: namrata AT
iastate.edu
- Office: 3121 Coover Hall
- Phone: 515-294-4012
- Problem Solving/Recitations:
12-12:30pm Tues or Thurs as needed
- Help
Sessions: Every alternate
Tuesdays, 5:10 - 6:30 pm. Students bring their problems or email me
problems they want discussed.
- Next help
session: Nov 14 (in my office 4-6 pm, come as a group anytime with
questions).
- NOT IN 1134 Sweeney
- Teaching
Assistant:
Shan
Yang
- Office Hours:
Monday 3:30-4:30pm, Thurday 8:30-10:00am
- Email: shanyang
AT iastate.edu
- Location: 119
Snedecor Hall (Statistics dept)
- Feedback: Your feedback
is welcome (e.g. is class going too fast or too slow), please email me (namrata AT iastate.edu). Put
"Feedback" in the subject line.
- Questions: You can come
to office hours or you can email me your questions and/or come to help
sessions. Put "Question" in
the subject line.
- Books:
- Text: Bertsekas &
Tsitiklis, Introduction
to Probability, Athena Scientific, 2002
- Supplementary Text:
Cooper &
McGillem, Probabilistic Methods of Signal and System
Analysis, Oxford, Third edition
- Other references:
- Yates, Probability and Stochastic Processes: A
Friendly Introduction for Electrical and Computer Engineers, John
Wiley & Sons, 1998.
- Ross, A First Course in Probability, 6th ed. Prentice
Hall, 2001.
- Papoulis, Probability, Random Variables and Stochastic
Processes, 4th ed., McGraw-Hill, 2001.
- Prerequisites:
EE 224, Basic calculus & linear alegbra. You should be
familiar
with basic calculus, e.g. you should be able to sum and integrate
common sequences and functions, e.g., sum a geometric progression and
integrate constants, exponentials, and sinusoids. You should be
familiar with elementary linear algebra, e.g. understand vector and
matrix notation and be fluent with simple operations with matrices and
vectors. You should also be familiar with the ideas of an inverse of a
matrix and the determinant of a matrix.
- Grading policy (Tentative)
- Homeworks
& Quizzes: 20%
- Midterm
Exam: 30%
- Final
Exam: 50%
- Homework and Quiz Policies (latest)
- In most cases, one Homework every week
- In most cases, one Quiz every alternate week
- In most cases, homework will be due on Thursday
- Grading for homeworks and
quizzes (20% weightage)
- Every homework will be graded out of 20.
- Every quiz will be graded out of 10.
- Points out of 20 = average Quiz points + (average Homework
points)/2
- Copying in homeworks:
You should solve first and discuss only after you submit. If you do
discuss and solve, please write names of
all students you discuss with. If you come to office hours to ask a
question about the homework, then you mention that too.
- Late
homeworks policy:
- Homeworks are due in class on
the assigned date. Anything submitted after the end of class will be
considered late.
- Late homeworks submitted upto 1 day late
(i.e. until 12:15 on the day after the due date) will be graded
out of 50% of the total points (i.e. if maximum points is 20,
you will be graded out of maximum points = 10).
- Anything
later than 1 day after the due date will get zero points
- Outline
& Syllabus
- Disability accomodation: If you have a documented disability and
anticipate needing accommodations in this course, please make arrangements to
meet with me soon. You will need to provide documentation of your
disability to Disability Resources (DR) office, located on the main
floor of the Student Services Building, Room 1076or call 515-294-7220.
- Library
Reserve List: will be posted
when available.
- Homeworks
(Maximum points is 20 unless otherwise specified)
- Homework 10
(Due date postponed, due Thursday Nov 30)
- Chapter 4 of
Supplementary Problems: Problems 30, 37, 38, 39
- Read
Section 4.5 and 4.6 of the book before attempting the HW
- MATLAB
verification of Problems 15 & 17 (which you did in HW 9)
- Homework 9
(Due Friday Nov 17): Total of 5 problems and MATLAB verification for
the last two.
- Chapter 4
of
Supplementary Problems: Problems 1,2,3,15, 17
- Problem 15,
17: Do by hand and verify in MATLAB
- Problem
17: you will have to discretize the PDFs before you can use the conv
function
- Thumb
rule: discretize at 8-10 times the Nyquist rate
- For
signals which are not bandlimited: use the 10% band (region where the
Fourier transform goes to 10% of its maximum value) as the approx
bandwidth
- MATLAB
verification can be submitted after Thanksgiving break
- Homework 8
(Due Thursday Nov 9 after deadline extension): Total of 6 problems, 5
will be graded
- Homework 7
(Due Thursday, Oct 26): Total of 6 problems
- Chapter 2 of
Supplementary Problems: Problems 14, 16, 18, 20
- Derive the
variance of a
geometric random variable (show all steps).
- Write the
proof for the
total expectation theorem.
- Homework 6
(Due Thursday, Oct 19): Total of 8 problems, 4 are for
credit, 1 for extra credit, 3 (book problems) for completion
- Chapter 3 of
Supplementary Problems: Problems 6,7, 8
- Problem 6
- Confusing language: it
should have been: A radar "often" tends to over-estimate the distance
of the aircraft
- Problem 8
- Typo:
Replace X by Z
- Skip part
(a) (since we
haven't done conditioning for continuous r.v.'s)
- Just do
part (b) directly
using total probability theorem applied to the event {1 < X < 3}
- Chapter 2 of
Book (NOT
SUPPLEMENTARY): Problems 25, 26, 31. Not for credit.
- Problem 26
- Note the
fact that "all
answers are equally likely to be picked". Explain the solution clearly.
- Problems 26
& 31:
Interesting & non-trivial problems to solve. Have fun.
- Chapter 2 of
Supplementary Problems: Problems 12, 13. Problem 13 is extra
credit
- Problem
12
- First
write the definition of joint PMF in terms of events
- Then
use what you know from Chapter 1 about computing the probability of the
intersection of two events.
- Are the
two events indepedent or not?
- Problem
13
- First
write the definition of joint PMF in terms of events.
- What is
the number of ways you can partition n into x, y and n-x-y parts.
Use the last formula on Page 48
- Homework 5
(Due
Tuesday Oct 3):7 problems, any 5 will be graded (same 5 for
all students of course)
- Chapter 2 of
Supplementary Problems: Problems 6, 7, 8
- Problem 6:
note that expected
time between successive bites is same as expected time until the first
bite.
- Chapter 3 of
Supplementary Problems: Problems 1, 2, 3
- 7th problem: Compute variance
of a
Poisson r.v. and of an exponential r.v.
- NO LATE HW ALLOWED (since I'll
give out
solutions on Tuesday itself)
- Homework 4
(Due Tuesday Sept 26)
- Chapter 1
of BOOK (not Supplementary Problems): 13, 14, 27
- Chapter 2
of BOOK (not Supplementary Problems): 4, 14
- Even
though solutions are available, I would expect you to either do them
yourself, or see the solution but write it clearly and in FULL
DETAIL WILL ALL THE STEPS.
- Homework
will be checked for completion (5pts) and the point is for you to
figure out for yourself where you're getting stuck and doing the
problem wrong
- Homework 3
(Due Tuesday Sept 19)
- Homework
2 (Due Tuesday Sept 12)
- Chapter 1 of
Suplementary Problems: Problems 18,
19, 23, 35, 28, 33
- Ungraded:
28, 33
- Graded:
18, 19, 23, 35
- Grading policy (out
of 20 pts): 5
pts for each of the 4 graded problems.
- Homework
1 (Due Thursday Aug 31):
- Grading
policy
(out of 20 pts):
4 pts for completion (completed 3,5, attempted 7,9,14,13). 4 pts
each for problems 7,9,14,13.
- Quiz and
Exam Dates
- Final
exam: Dec 12 (Tuesday)
- Syllabus:
Chapters 1,2,3, Chapter 4: 4.1,4.2,4.5,4.6,
- Hypothesis
testing: you don't need to remember anything. I may give a question
which only requires knowledge of the above syllabus but has application
in hypothesis testing, e.g. compute the type 1 error probability of a
certain test (the test will be specified and so will the formula for
computing type 1 error probability)
- Make-Up
Midterm exam (Dec 7)
- Make Up Exam Solution
- Syllabus:
Everything from Chapters 1, 2 and 3
- Quiz
8 (take home quiz): Quiz 8 solution
- Due Friday Nov 17
by 5pm
in my office.
- QUIZ 8:
Thursday Nov 16
- Quiz 7 (take
home quiz): Due Wednesday Nov 8 by
5pm in my office
- Quiz
7:Tuesday Nov 7
- Ch 3: 3.4,
3.5, 3.6 (whatever covered in Oct 31 class)
- Quiz 6:
Thursday October 26
- Ch 2: 2.6, 2.7, Ch 3: 3.4 (whatever covered in Oct 24 class)
- Quiz 5:
Thursday October 19
- 15 minute
Quiz 11:05am - 11:20 am: COME ON TIME
- Gaussian
pdf (3.3), Joint & Marginal PMF of multiple discrete r.v.s ,
Expectation of functions of 2 or more r.v.s (2.5)
- Midterm Exam:
Thursday October 5 (email me if you have a very strong reason this date
does not work)
- Quiz 4:
Tuesday October 3
- Ch 2:
2.1-2.4, Ch 3: 3.1-3.2 (knowledge of concepts of Ch 1 is needed for
everything)
- QUIZ WILL
BEGIN at 11:10am, please come on time.
- Quiz 3:
Thursday September 21
- Chapter 1 and Chapter 2:
2.1 - 2.3
- Quiz 2:
Thursday, September 14
- Everything
from Chapter 1
- Quiz 1: Thursday, 8/31
- Everything
taught until and on 8/29.
- Handouts and
Other Useful Links
- These DO NOT replace the book. In
most cases, they only provide a guideline on topics and an intuitive
feel. The math details will be covered in class, so it is important to
attend class and also you MUST read the book)
- Read
Ahead List
- For Thurs 8/24: Read until Conditional Probability in
Chapter 1
- For 8/29 and 8/31: Finish reading Chapter 1 and Handout 1.
- For 9/5: Revise Chapter 1.
- For 9/7: Bring Handout 2 and read 2.1 and 2.2 from the book
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Vaswani's homepage