**
Quantitative Ecology & Evolution (Multivariate Statistics) 215:575; **

**
SYLLABUS 2007**

Sept.
7
INTRODUCTION ; DATA
Chapter 1

14
DESCRIPTIVE STATISTICS;

CLUSTERING VS.
ORDINATION Chapter 1

21
BASIC CLUSTERING

ALTERNATE CLUSTERING METHODS
Chapter 3

28
No Class – PJM away

Oct. 5
No Class – PJM away

12
CHOOSING CLUSTERING METHODS
Chapter 3

CLUSTERING WITH SAS

19
MATRIX ALGEBRA
Handout

LINEAR TRANSFORMATIONS
Chapter 2

26
PCA
Chapter 2

PCA WITH SAS

Nov. 2
DIVISIVE CLASSIFICATION
Chapter 5

CANONICAL CORRELATION

9
M.V. HYPOTHESIS TESTS
Chapter 4 & Handout

16
MANOVA
Chapter
4 & Handout

23 No Class
– Thanksgiving Break

30 MANOVA & DISCRIMINANT
ANALYSIS Chapter 4 &
Handout

Dec. 7
REPEATED MEASURES ANALYSIS
Handout

Project I is due on 26 Oct. Project
II is due on Dec. 7 See reverse for details

TEXT:
McGarigal, K., S. Cushman,
and S. Stafford. 2000. Multivariate Statistics for Wildlife and Ecology Research.
Springer,

P. J. Morin; e-mail: **pjmorin "at" rci "dot"
rutgers "dot" edu** , office - ENR 148, phone 2-3214

**
Quantitative Ecology and Evolution (MULTIVARIATE STATISTICS) - 215:575**

**
PROJECT I:**

1. The goal of your FIRST project
is to gain familiarity with the scientific literature involving one or more
methods of multivariate statistical data analysis.
The project involves writing a short essay (5-10 pages max. less
references, typed, double-spaced) reviewing the use of one or more types
of multivariate analysis in ecology or evolution.
The essay should focus on the specific attributes of a given class
of techniques, and should emphasize the ecological or evolutionary interpretation
of the technique. Potential topics
include cluster analysis, ordination, discriminant
analysis, or any other topics listed on the syllabus.

2. The project will involve
reviewing some of the original literature on a given topic.
References listed in the bibliography of your text should offer
a useful entry point into the literature. This is not meant to be an onerous
time-consuming exercise. Use it to your advantage to learn about an approach
that you plan to use in your own research.

**
PROJECT II:**

1. The goal of your SECOND project is to gain familiarity with one or more
methods of MULTIVARIATE data analysis, *
USING SAS. *Ideally, the analysis
should be of your own data. If you
lack data, we can provide you with some.
The analysis should describe some aspect of the data set that is not
obvious from simple inspection. Possibilities
include a cluster analysis of community samples describing species abundance
patterns, analysis of spatial patterns, ordinations of small data sets,
discriminant analysis of differences between sets of samples, etc.

2. Your analysis should be described in a short (10 pages max., typed, double-spaced)
report divided into the following sections:

**
A. INTRODUCTION**
: briefly describe the phenomenon that you are analyzing, and the questions
that you attempted to answer.

**
B. MATERIALS AND METHODS**
: describe the data, how the data were collected, the analytical techniques
used, and why those techniques were selected.

**
C. RESULTS**
: concisely describe the outcome of the analysis.
One table or figure can and should replace many pages of prose.

**
D. DISCUSSION**
: interpret the biological significance of your results.

**
E. LITERATURE CITED**
: list any references cited in the text of your report. See a recent issue
of the journal ECOLOGY

**
F. APPENDIX**
: append copies of your raw data, computer output, and/or any additional calculations.

2