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