This will be a modern graduate course in statistics
for life science and biomedical students. We will present the most popular
statistical tools for data analysis and support those with an elaborate framework
of simulations, applets, compute-engines, movies and real-time Internet tools.
A number of course projects (papers) will help the students gain a
hands-on experience on design of scientific experiments,
data acquisition, processing, integration, statistical analysis and presentation.
Textbook: Statistical Research Methods in the Life Sciences, by P.V. Rao, Duxbury Press (1998).
Tentative order of topics covered
Variables, measurements, statistics and parameters.
Normal, Binomial and Poisson distributions.
Basic statistics, 5-number summaries.
Central Limit Theorem.
Inferences About One Or Two Populations.
Design of studies and experiments.
Analysis Of Variance (ANOVA).
Regression and Correlation.
Principle component analysis (if time permits!).
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Ivo D. Dinov, Ph.D., Departments of Statistics and Neurology,
UCLA School of Medicine