ECE 313 Late-Breaking News

- You are allowed to bring ONE 8.5" by 11" sheet of notes to the exam;
both sides of the sheets can be used.

Calculators, laptop computers, Palm Pilots and the like are not permitted. - You are expected to know what is meant by
- a Bernoulli random variable with parameter p
- a binomial random variable with parameters (n,p)
- a geometric random variable with parameter p
- a Pascal or negative binomial random variable with parameters (r,p)
- a Poisson random variable with parameter (lambda)

- a Bernoulli random variable with parameter p

Material covered on the examination is all that was covered in class through Thursday July 2. In terms of the text, we have covered everything on Reading Assigment sections of Homeworks 1 through 3. In terms of Problem Sets, Problem Set 1, 2, 3, and Part 1 (First four problems) of Problem Set 4 are included. If you are following along in the Powerpoint slides on the class web page, we have covered Lectures 01-14 thus far.

- You are allowed to bring ONE 8.5" by 11" sheet of notes to the exam;
both sides of the sheets can be used.

Calculators, laptop computers, Palm Pilots and the like are not permitted. -
### The Phi function table

(Area under the unit Gaussian), as well as some useful mathematical identities will be provided in the exam booklet. - Material covered on the examination is all that was covered in class through Wednesday July 23 (Bivariate Random Variables are not included). In terms of the text, we have covered everything on Reading Assigment sections of Homeworks 1 through 6. In terms of Problem Sets, Problem Sets 1 through 6, as well as first two problems of Problem Set 7 are included. If you are following along in the Powerpoint slides on the class web page, we have covered Lectures 01-14, 18-29 thus far. Note that we have covered some extra material in class that is not covered in the slides.

- You are allowed to bring TWO 8.5" by 11" sheets of notes to the exam;
both sides of the sheets can be used.

Calculators, laptop computers, Palm Pilots and the like are not permitted. - You are expected to know what is meant by
- a Bernoulli random variable with parameter p
- a binomial random variable with parameters (n,p)
- a geometric random variable with parameter p
- a Poisson random variable with parameter (lambda)
- a random variable uniformly distributed on (a,b)
- an exponential random variable with parameter (lambda)
- a gamma random variable with parameters (t, lambda)
- a Gaussian random variable with mean (mu) and variance
(sigma)
^{2} - a bivariate random variable (X,Y) uniformly distributed on a region of the plane

- jointly Gaussian random variables with means (mu)
_{x}and (mu)_{y}respectively, variances (sigma_{x})^{2}and (sigma_{y})^{2}respectively, and correlation coefficient (rho)

A table of values of the unit Gaussian CDF will be supplied to you if it is needed on the exam.

Material covered on the examination is all that is covered in class through Wednesday August 7 (You are not required to know the proof of the Central Limit Theorem.). In terms of the text, we have covered everything on Reading Assigment sections of Homeworks 1 through 8. All Problem Sets are included. If you are following along in the Powerpoint slides on the class web page, we have covered Lectures 01-14, 18-36, 38-41. Note that we have covered some extra material in class that is not covered in the slides. Specifically, the Poisson Points Experiment, and Bayesian Estimation are not in the slides. You are not required to know the proof of the Central Limit Theorem (Slide 41), but its implications, such as De-Moivre Laplace Theorem are included.

- a Bernoulli random variable with parameter p