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Statistics is concerned with methods for discovering and confirming
in data, patterns that are partly (perhaps largely) obscured by random
noise. The field of statistics, like other areas of applied mathematics,
acts as a clearing-house for data-analytic ideas: developing, understanding,
abstracting, and packaging them for general use in areas remote from
their origins. It is not necessary---or sufficient---to have majored
in mathematics as an undergraduate in order to become a statistician.
In fact, the diversity of applications of the subject can make it
a positive advantage to have majored in another field.
To boast for a moment about our faculty, we have four members of the
National Academy of Sciences, two of the Institute of Medicine, three
MacArthur `genius' prize fellows, and among younger faculty, three
Presidential Investigator Award winners. We are consistently ranked
together with (or ahead of!) our friends and archrivals at Berkeley
as the leading statistics department in the U.S.
The Stanford Center for Professional Development, in its commitment
to extend Stanford research and teaching to students in industry,
has developed this portfolio of courses and programs in statistics.
Students in industry take these courses as pre-requisites for courses
in electrical engineering and other fields, as part of their education
in biostatistics and for its application to their work — managing
risk, analyzing customer data, designing investment portfolios and
more.
Bioinformatics
Computational Genomics
Data Mining and Applications
Quantitative Methods in Finance and Risk Management
STAT110 Statistical Methods in Engineering and the Physical Sciences
STAT116 Theory of Probability
STAT202 Data Analysis
STAT237 Time Series Modeling and Forecasting
STAT240 Statistical Methods in Finance
STAT243 Introduction to Mathematical Finance
STAT252 Data Mining and Electronic Business
STAT315A Modern Applied Statistics: Learning
STAT315B Modern Applied Statistics: Learning
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