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The objective of this course is to
enable students to analyze and model data using statistical
and graphical methods.
The expected learning outcomes of this class are:
- Students will be able to explain the fundamentals of
probability theory and graph theory, and apply relevant concepts to
describe, model, and analyze data sets.
- Students will be able to present analyze and model data sets
by applying knowledge from topics including probability distributions,
Bayes theorem, conditional independence, discrete and continuous models,
regression models, hypothesis testing, and Markov chain methods.
If time permits, time series analysis and ARMA models will also be discussed.
The class will require graduate standing
and preferably have taken CE5690 and/or CE5390. In addition, students are expected
to come with an an open mind. Computer programming experience will be useful,
but not necessary.
The class meets thrice every week:
Lectures: ??
Office hours: Open door policy!
Amlan Mukherjee
2007-09-03