EE 322 (STAT 322): Probabilistic Methods for Electrical Engineers
The course will cover descriptions of discrete and continuous random variables (probability mass function, cumulative distribution function and probability density function); mean and variance computation; conditioning and Bayes rule; statistical independence; and joint, conditional and marginal pdf and cdf. Bernoulli, Binomial, Geometric, Poisson, Uniform, Exponential, Gaussian and other distributions of interest to EE students will be discussed. Moment generating functions, PMF, PDF of sums or random variables will also be covered. Covariance, correlation and Bayesian least squares (and linear least squares) estimation will be covered. Markov and Chebyshev inequality, law of large numbers, central limit theorem.  Time permitting, we will also introduce basic concepts of (a) Monte Carlo and importance sampling and (b) Markov chains.

Grading, Attendance, Late Homework Policy

Homeworks

Handouts

Class/Quiz/Exam Schedule & Syllabus

• Announcements
• HELP SESSION on MONDAY OCTOBER 6 in 1219 Coover, 5-6pm
  
• First midterm exam on Tuesday October 7 (based on Chapter 1, 2.1 - 2.4)
  
• Second handout posted - this is a long one
  
• We will follow the old edition (edition 1) of the textbook: available at the Campus Book Store
  
• Grading, Attendance, Late Homework Policy
• Class/Quiz/Exam Schedule & Syllabus
• Handouts
• Class time and Location:  Tuesday-Thursday 11:00-12:15, Location: PHYSICS 0003  COOVER 1016 
• Instructor: Prof. Namrata Vaswani
  
• Office Hours:  Tuesdays 4-5pm,  Fridays 2-3pm or by appointment
  
• Email: namrata AT iastate.edu  
  
• Office: 3121 Coover Hall
• Phone: 515-294-4012
• Teaching Assistant: Shurui Huang
  
• Email:  hshurui AT iastate.edu
  
• Help Session/Recitation Hours: Wednesday 5-6pm (she will run a recitation/help session which is not-mandatory but highly recommended)
• Location: 1011 Coover Hall (new wing of Coover)
• Webpage/WebCT: Handouts and Important Announcements will be posted on class webpage. WebCT will be used for homeworks and solutions and grades
  
• Textbooks/References:
• Text: Bertsekas & Tsitiklis, Introduction to Probability, Athena Scientific
• First chapter downloadable  from  http://www.athenasc.com/Ch1.pdf
• Textbook errata: http://web.mit.edu/6.041/www/prob-errata.pdf
  
• Other references:
  
• Yates and Goodman,  Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers, John Wiley & Sons, 1998.
• Cooper and McGillem, Probabilistic Methods of Signal and System Analysis, Oxford, Third edition
• Ross, A First Course in Probability, 6th ed. Prentice Hall, 2001
• Class Information Sheet
• Disability accommodation: 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 1076, 515-294-7220.
• 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.
• Prerequisites: EE 224, Basic Calculus and 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.