Download Biol 325 - Ecological Analyses

Winter 2009
1
NRES 798 – Analysis of Ecological Data
College of Science and Management, University of Northern British Columbia
Instructor: Dr. Michael Gillingham, 8-312, 960-5825, [email protected]
Course Webpage (in part): http://web.unbc.ca/~michael/Courses/Biol325.htm
COURSE DESCRIPTION
This course is an introduction to the application of analytical methods for addressing common ecological
problems. Particular emphasis is placed on: working with data, testing assumptions, formulating hypotheses,
statistical inference and the discussion of the application of these statistics. Students learn to analyze and interpret
ecological data using a variety of statistical analyses. In addition to lab material, graduate students in this course
will apply suites of analyses to data applicable to their area of research.
LECTURES
There are two components to the lectures. Students will attend all Biol 325 Lectures (Tuesday and Thursday from
9:30 - 10:20 in 5-171). These lectures introduce the principles of experimental design and ecological sampling,
and discuss the basic statistical methods used to analyze experimental ecological results. In addition, we will
meet for 2 hours per week (Wednesday from 8:30 to 10:20 (Room TBA) to discuss more sophisticated
applications of the analysis techniques.
LABS
Graduate Students in NRES 798 should enrol Biol 325 Lab Section L2 (CRN# 10244 on Monday from 8:00 to
10:50 in room 7-154). The labs will emphasize hands-on statistical analysis and interpretation of results from
quantitative observations and manipulative experiments. Analysis will be done with statistical packages
(primarily SAS). Assignments arising from the labs will require students to complete data analyses and to submit
their results along with a scientific abstract that summarizes their findings and conclusions, emphasizing the
interpretation of the analyses.
STUDENT MARKS


Ten assignments will be assigned from laboratory exercises; each assignment will be worth 4% of the grade
for a total of 40% of the final grade. Assignments will combine the analysis and interpretation of ecological
data and will usually include summarizing the results in a scientific abstract. These assignments will usually
be due one week later at the beginning of class/lab; late problem sets will NOT be accepted.
Working with the instructor, students will develop an analysis strategy to examine data relevant to their
research area (supplied by thesis supervisor). These analyses will be developed into two projects with each
project comprising 30% of the final grade. The projects will involve the application of techniques covered in
the course (Project 1 due on 3 March will cover analyses addressed in labs 1 through 6; Project 2 due on 15
April will utilize analyses covered in labs 7 through 12). Each project will be submitted as a report, in journal
format, that is supported by the analyses.
INSTRUCTOR’S OFFICE HOURS

My office hours are Monday and Wednesday from 11:00 to 12:00 (8-312; new lab building). Your cooperation in visiting during these office hours is appreciated. If you need to see me outside these hours, please
make an appointment in advance (960-5825 or [email protected]).
TEXT BOOKS (Required)
Gotelli, N.J., and A.M. Ellison. 2004. A Primer of Ecological Statistics. Sinauer Associates Inc., Sunderland, MA.
PREREQUISITES: Permission of the Instructor
ACADEMIC DISHONESTY INCLUDING PLAGIARISM
University regulations strictly forbidden academic dishonesty of any type, including plagiarism, cheating during
tests or exams, or misrepresenting the nature of your involvement in any assigned work. Students involved in any
such acts can receive an automatic F in the course.
Winter 2009
2
TENTATIVE LECTURE TOPICS
DATE
Gotelli
6-Jan
Introduction, Grading, Course Objectives; A review of probability
4-24
8-Jan
Random Variables and Probability Distributions
25-55
13-Jan
Measures of Location and Spread
57-78
15-Jan
Checking the Data
207-224
20-Jan
Meeting Assumptions: Outliers and Transformations
224-236
22-Jan
Framing and Testing Hypotheses: Statistical Hypothesis Testing
79-106
27-Jan
Tests of Differences: two unrelated samples
29-Jan
Pseudoreplication, Error, Power, Parametric or not?
3-Feb
Tests of Differences: two related samples
5-Feb
Overview of Experimental and Sampling Designs
10-Feb
Tests of Relationship: Correlation
12-Feb
Midterm for Biol 325 (no class for NRES 798)
163-204
Winter Break - No Classes Feb 16-20
24-Feb
Tests of Relationships: Regression
240-264
26-Feb
Multiple Regression and non-linear Regression
275-279
3-Mar
Logistic Regression; First Project Due
273-275
5-Mar
ANOVA: one-way and Kruskal-Wallis ANOVA
289-300
10-Mar
More ANOVA designs: Nested and two-way ANOVA
300-308
12-Mar
ANOVA Designs Continued
17-Mar
More ANOVA designs: Split Plot and Repeated Measures ANOVA
308-314
19-Mar
Random versus Fixed Effects; Analysis of Covariance
314-322
24-Mar
Tests of Categorical Data: Contingency tables, 1- and 2-way Classification
349-382
26-Mar
More on Classification
31-Apr
Alternate Frameworks for Statistical Analyses
2-Apr
Choosing the Correct Test: a review
7-Apr
Review continued
15-Apr
Second Project Due
“
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107-134
Winter 2009
DATE
3
TENTATIVE LAB TOPICS (5-154)
12-Jan
A gentle introduction to SAS
19-Jan
Data Manipulation and Describing Data (Assignment #1)
26-Jan
Testing and Meeting Assumptions: test for homogeneity of variance; transformations
(Assignment #2)
2-Feb
Comparing two populations: unrelated samples (Assignment #3)
9-Feb
Comparing two populations: related samples (Assignment #4)
23-Feb
Correlation (Assignment #5)
Winter Break - No Classes Feb 16-20
2-Mar
Regression (Assignment #6)
9-Mar
Multiple Regression and Non-linear Estimation (Assignment #7)
16-Mar
Parametric and non-parametric One-way ANOVA (Assignment #8)
23-Mar
Randomized Blocked and Two-way ANOVA designs (Assignment #9)
30-Mar
ANOVA with non-standard F-ratios and Planned and Unplanned Comparisons
(Assignment #10)
6-Apr
Goodness of Fit: goodness of fit (2), contingency tables (G) and tests of
independence