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POST-CONFERENCE SHORT COURSE
II*
TAKING MULTIVARIATE STATISTICAL METHODS
OUT OF THE BLACK BOX
Wednesday, August 23
2-5pm
1:30
Registration for Afternoon Short Courses
2:00-5:00
Taking Multivariate Statistical Methods of the Black Box
Ms. Janis Dugle, Senior Research Scientist (Statistics), Ross Products
Division, Abbott Laboratories
The multivariate statistical methods of Principal Components Analysis (PCA),
Partial Least Squares (PLS) and Discriminant Analysis (DA) have become
popular tools of the burgeoning biosytems and “omics” sciences
(genomics, proteomics, metabonomics, etc.). However, they often appear
as “black box” techniques that leave the scientist in the dark about
what has been done to his/her data. This mini-course provides a
non-technical introduction to these methods. Many examples of PC, PLS
and DA are given (sometimes on the same data), which allows comparisons
of their capabilities, limitations, and commonalities. Many sources of
data are used to illustrate the wide range of application of these
techniques, and the resulting graphical output gives a hands-on feel to
large data sets. The course ends with a grand finale of a marker search
through data with thousands of measurements on 116 samples. This class
is enjoyable and easily understood, regardless of your statistical
background.
Who
should attend?
This course is designed for anyone who wants a non-technical,
understandable, highly visual overview of PC, PLS, and DA. It is
appropriate for the researcher who is interested in seeing what
statistics can and can't do, but who is not concerned with technical
statistical derivations.
Why
attend?
Do you want to be able to “talk the talk” in multivariate methods?
This is the place. Find out what they are doing with your data, and what
other options may be available.
5:00-6:00
Early Registration For Microarray
Data Analysis Meeting
*
Separate Registration Required
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