An in-depth discussion of the concepts and systematic 
development of the theory of experimental design will be
emphasized. The students will obtain a thorough understanding of
the basic concepts in design of experiments, including
experimental and observational units, randomization, blocking 
and replication.  They will be exposed to different kinds of
experimental designs along with their strengths and weaknesses.
They will learn how to search for, or construct efficient
experiments, analyze and interpret the data collected from those
experiments with the help of advanced statistical software 
packages.

The course will cover the following topics: analysis of variance and covariance; completely randomized designs; randomized complete block and incomplete block designs; multi-way layout; row-column designs; repeated measures designs; cross-over designs; non-regular designs; full factorial and fractional factorial designs; designs involving both quantitative and qualitative factors at different levels; split-plot experiments; non-regular designs; designs for generalized linear models; approximate design theory and algorithms; online experiments; global optimization; and computer experiments with space-filling designs. At the discretion of the instructor, additional topics may be covered.