Training
Announcement
Multivariate Statistical Analysis Techniques for Ecological Data using R
(FIS4400)
Course Dates: January 10-14, 2011
Location: NCTC, Shepherdstown, WV
Course Description/Course Overview:
This course covers a variety of descriptive and inferential multivariate
statistical methods that are useful for analyzing biological data.
Participants will be using program R (R Foundation for Statistical
Computing, free software) to analyze ecological data and apply the various
multivariate procedures in a computer lab setting. Several case studies of
multivariate techniques applied to field data are discussed.
Course Objectives: Identify the basic concepts of matrix algebra,
eigenvalues, eigenvectors, and multivariate normality. Demonstrate methods
for displaying relationships and position (principal components analysis,
factor analysis, biplot displays, correspondence analysis, multidimensional
scaling, and cluster analysis). Perform procedures for group separation
(MANOVA, canonical variate analysis, discriminant analysis, logistic
regression). Describe techniques for determining relationships between
sets of variables (canonical correlation analysis and canonical
correspondence analysis); and analyze repeated measures.
Instructor: Eric Smith, Department Chair
Statistics Department, Virginia Tech.
Who Should Attend: Biologist and researchers who are involved in
monitoring or studies associated multi-variable data?
Course Length: 4 and ½ days/36 hours
Prerequisites: No specific pre-requisites, but it is assumed that you
have taken one or more courses in statistics.
Classroom: G24 Computer Lab (National Conservation Training
Center (NCTC).
Cost: There is no tuition fee for FWS, NPS, and BLM personnel. Tuition is
$1050 for other participants.
How to Apply: Register on-line at https://doilearn.doi.gov/. Non-DOI
employees should download the application form at
http://training.fws.gov/learn/courses.htm
Closing date for applications: November 15, 2010
Questions: Please contact Joe W. Witt ([email protected]) or So Lan Ching
([email protected]), Branch of Conservation Science and Policy, at
304/876-7447 or 304/876-7771.
