ECE 313 Exams

Fall 2008

You may bring one 8.5" by 11" sheet of notes to each hour exam; 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 September 24 and 26.

You can find copies of old hour exams by going to the web pages of previous offerings of ECE 313.

Room assignments are as follows:

- Last names beginning with A-D, Room 260 Mechanical Engineering Building
- Last names beginning with E-K, Room 335 Mechanical Engineering Building
- Last names beginning with L-Z, Room 253 Mechanical Engineering Building

Students who are registered in ECE 313 AND in ECE 410 (whose final exams are at the same time as those of ECE 313) should take the Final Exam for ECE 313 from 1:30 p.m. to 4:30 p.m. and the Conflict Final Exam for ECE 410 from 7:00 p.m. to 10:00 p.m. These instructions also apply to students registered in ECE 313 AND ECE 410 AND ECE 440. Such students should also supply their ECE 440 instructor with their COMPLETE Exam schedule so that the ECE 440 Conflict-of-Conflict Exam can be set up. Students registered in ECE 313 AND ECE 440 but not in ECE 410 should take the Final Exam for ECE 313 from 1:30 p.m. to 4:30 p.m. and the Final Exam for ECE 440 from 7:00 p.m. to 10:00 p.m.

- You are allowed to bring THREE 8.5" by 11" sheets of notes to the exam;
both sides of the sheets can be used, but the exam is closed-book
and closed-notes otherwise.
Electronic devices (calculators, cellphones, pagers, laptops, etc.)
are neither necessary nor 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 random variable uniformly distributed on (a,b)
- an exponential random variable with parameter (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