COURSE DESCRIPTION
Introduction to concepts of probability distribution functions, moments,
statistical dependence, and an introduction to statistical methods. Course
emphasizes application to physical problems.
PRE-REQUISITE :
POST-REQUISITE : EE 4220, EE 4341,
EE 4388, EE 4365
COURSE OUTCOMES :
Students completing EE3384 will be able to :
- Solve basic counting problems involving permutations
and combinations of equally-likely events (I).
- Use elements of set theory and axioms of probability to determine the probability of complex events, and
apply Bayes Theorem to the solution of conditional
probability problems (C).
- Solve problems involving independent events and
independent random variables (C).
- Determine marginal and joint cumulative distribution functions (CDF), probability mass functions (PMF)
and probability density functions (PDF) and use them
to compute various expected values of discrete and continuous RV’s
(C).
- Solve problems involving Gaussian, uniform, exponential, binomial and Poisson RV’s (C).
- Compute PDF’s and CDF’s of a function of a random variable (I).
- Compute expected values of sums of RV’s and the covariance and correlation of pairs of RV’s
(C).
- Use the Central Limit Theorem, significance tests and hypothesis test in introductory statistics problems (I).
PREVIOUS COURSE NUMBER:
RESPONSIBLE COMMITTEE:
Communications
PREVIOUSLY OFFERED
| FALL |
SPRING |
SUMMER |
| all |
all |
- |
TO BE OFFERED (Tentative)
| FALL |
SPRING |
SUMMER |
| 2001 |
2002 |
- |
| 2002 |
2003 |
- |
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