Course Outline
DAY
1
Intro
to Multivariate Methods
goals and objectives
of each
availability of
software
Graphing Multivariate Data
visualizing patterns
in 3 and more dimensions
Exercise: Graphing
SO2 data
Principal Component Analysis
what PCA
accomplishes
how PCA is
computed
Exercise: PCA for
differentiating species patterns between sites
Factor Analysis
what FA accomplishes
and cannot accomplish
differences between
FA and PCA
Exercise:: Factor
Analysis on species patterns
Correspondence Analysis
CA objectives
relation to
contingency table tests
plot of
associations
Detrended CA
Exercise:
Correspondence Analysis on microcrustaceans
DAY 2
Cluster Analysis
Methods of
clustering. Linkages
How well can known
clusters be identified?
Determining the
number of clusters
Exercise: Clustering
sites by chemical and species patterns
Discriminant Analysis & Logistic Regression
How to classify
observations.
Assumptions
involved
Exercise: DFA &
Logistic on SO2 data
Canonical Correlation and Canonical Correspondence Analysis
Correlations between
sets of variables
What can and cannot
be accomplished
Exercise: Canonical
Correlation
Nonparametric Methods
Nonmetric
Multidimensional Scaling
Nonparametric MANOVA
to differentiate groups
Multivariate
trends
Determining which
variables contribute most to group differences