This is supplemental course information, designed to give you a fuller picture of the course and an expanded look at the topics covered. This is an unofficial document. The USC Course Catalog is the binding description of all university courses. Information such as books, materials covered, and the order of topics is subject to change. Please consult instructor for this semseter to get more upto date course information.
2006-07 Catalog Data:
Introduction to concepts of randomness and uncertainty: probability, random variables, statistics. Applications to digital communications, signal processing, automatic control, computer engineering and computer science. Prerequisite: MATH 225 or MATH 245 or EE 241.
Textbook:
R. E. Walpole, R. H. Myers, and S. L. Myers, Probability and Statistics for Engineers and Scientists. Sixth Edition, Prentice Hall, New Jersey, 1998.
Coordinator:
E. Jonckheere, Professor, Electrical Engineering
.
Topics:
1. Introduction to probability: coin tossing, sample space, games of cards, Bayes’ law, binomial and multinomial laws, Stirling’s formula, De Moivre-Laplace formula; first formulation of central limit theorem.
2. Poisson distribution as the limit of the binomial distribution; application to radioactive counting and aircraft accidents.
3. Random variables, probability density, cumulative distribution, marginal density, conditional density. Gauss distribution.
4. Introduction to statistical physics: Maxwell-Boltzmann distribution.
5. Change of random variables.
6. Sum of random variables, convolution formula, characteristic (moment generating) function; elementary formulation of the central limit theorem.
7. Kolmogorov’s law of large numbers.
8. Estimation of mean and variance. Xi-square distribution. Confidence level.
9. Linear and nonlinear regressions, T-distribution. Confidence level.
10. Hypothesis testing.
Course objectives:
To introduce EE students to random phenomena at the Junior level, so that they would be able to apply probabilistic concepts at Senior level in such classes as solid state physics, random noise in electrical circuits, etc.
Course Outcomes:
The students will be able to
1. Formulate random phenomena in the context of probability theory.
2. Compute probablities of elementary random phenomena.
3. Compute continuous probabilities.
4. estimate mean and variances.
5. Do elementary regressions.
6. Compute confidence intervals.
Laboratory Project:
Design an experiment to confirm the central limit theorem.
Relations of the Course Outcomes to the EE Program Outcomes:
a,b,c,d,e,h,j,k,l,m,n
Prepared by: Edmond Jonckheere (jonckhee@eudoxus.usc.edu) , X04457.
