ECE 313 Exams

Spring 2010

Section C (Lectures at 10:00am): Room 165 EL.

Sections D and E (Lectures at 11:00am and 1:00pm): Room 314 Altgeld Hall (across the street from EL)

Section F (Lectures at 12:00 noon): Room 269 EL

Please go to the room according to the section you are registered for, not the section you are auditing (if those two do not happen to coincide). Please make sure that you bring your IDs with you, and that you show up at 15 earlier, in order to avoid last minute problems (such as not being able to find the room).

The conflict exam will be held from 5:30pm until 6:30pm in Room 241 EL.

Hour Exam II: Tuesday April 13, 7 pm to 8 pm, Locations TBA.

You may bring one 8.5" by 11" sheet of notes to the hour exams; both sides of the sheet can be used, but the exams are closed-book and closed-notes otherwise. Electronic devices (calculators, cellphones, pagers, laptops, etc.) are neither necessary nor permitted.

To compensate for evening hour exams, there will be no ECE 313 classes on Friday February 26 and Wednesday April 21.

First Hour Exam and its solution<\P>

Second Hour Exam solutionYou can find copies of old Hour Exams by going to the web pages of previous offerings of ECE 313.

Copies of some old final exams can be found by going to the web pages of previous offerings of ECE 313.

- By the time of the final exam, 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 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.

- a Bernoulli random variable with parameter p