Department of Environmental Sciences
Huxley College of the Environment
Western Washington University

ESCI 340 Biostatistical Analysis
Winter 2009
MW 9-11 AM ES 310
F 9-11 AM AH 5

Instructor: John McLaughlin Teaching Assistant: Andrew Shirk
Office: ES 434 Office: ES 430
Phone: 650-7617 Phone: 650-3254
E-mail:
Office Hours: MWF 1-2 Office Hours:

Course Web Site: http://www.ac.wwu.edu/~jmcl/Biostat/syl2009w.htm
Please note: some hyperlinks may not be activated until class time.

Text: (Recommended) J. H. Zar. 1999. Biostatistical Analysis, 4th ed. Prentice Hall
Additional readings available in course binder in Huxley Library, ES 545.

Prerequisite: one year of general biology.

It is easy to lie with statistics. It is hard to tell the truth without statistics.
-- Andrejs Dunkels

Course Description:
This course is an introduction to data analysis and statistical tests commonly used in the biological and environmental sciences. Much of the material will be developed with a series of exercises during which you will collect data to address research questions and analyze those data using appropriate methods. In a broad sense, the main objective of the course is to help you understand the principles, methods, and limitations of data analysis. After successfully completing the course, you should be able to identify appropriate applications of common statistical methods, to perform the methods competently, and to interpret statistical results critically.

Course Evaluation:
Grades will be based on homework assignments and three examinations. Homework assignments will comprise 50% of the course grade. Two "midterm" exams will contribute 15% each toward the course grade. The final exam will contribute the remaining 20%.

Homework:
Homework will be posted online to the links below, generally before class time on Friday.
It is due at the beginning of class the following Friday. Meet the deadline for full credit.

Homework Guidelines:
(1) Be clear, neat, complete, and concise. The teaching assistant has many assignments to grade;
it will be to your advantage to organize your work to make his job easier.

(2) Staple your work, if you submit more than one page.

(3) Put your name, course name, assignment number, and date submitted somewhere at the top of the first page.

(4) Show your work. Correct methods will be worth as much as correct answers. For full credit, show all formulas used. Numerical tools (calculators, spreadsheets, SPSS, R) often combine several steps their calculations; you must show formulas for each step. When you use SPSS or R computer programs, indicate commands or menu options that you used to obtain your results.

(5) For assignments based on data collected in lab, state assumptions that you made in your analysis.

Course Schedule:
Please note: some hyperlinks may not be activated until after class.

Week

Research Project

Jan. 7

Edge effects on tree growth
Traffic loads on Bellingham/WWU streets (Snowy weather alternative)

Jan. 12

Moss growth on maple trees

Jan. 19

Martin Luther King, Jr. Day -- No class

Jan. 21

Animal tracks: Minimal Outline vs. Variable Outline
Bike rack use in wet vs. dry weather
Repeat traffic loads project under snow/ice free conditions (Snow alternative)

Jan. 26 (Mon.)

Moss cover vs. substrate and aspect
Exam 1:
Wed. Jan. 28 (one page of notes permitted) study question answers
paired t-test problem and answers

Feb. 2

Differential moss cover
Herbaceous plant species composition in deciduous vs. coniferous stands

Feb. 9

Maple seed dispersal distances

Feb. 16

Presidents' Day -- No class

Feb. 18 (Wed.)

Exam 2: Wed. Feb. 18 (two pages of notes permitted)
study question answers
Spread of invasive plant species from roads and trails (after exam)

Feb. 23

The Mixed Nut Problem
Species richness in tidepools

Feb. 27 (Fri.)

Intertidal Field Lab: Meet at ES building garage doors
Species richness in tidepools

March 2

The Mixed Nut Problem (continued)
Species richness in tidepools (continued)

March 9

Course review: appropriate application of statistical methods; Answers
More review questions; Answers

March 13 (Fri.)

Final Exam: 9-11 am (four pages of notes permitted)

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Statistical Methods

Reading (from Zar)

Nomenclature
Distributions, random variables, and sampling
Selecting the appropriate hypothesis test

Ch. 1 - 6
Sections 24.1 - 24.3, 25.1

R information and software downloads
USGS site about R
R homepage
Probability Further reading
One-sample hypothesis tests
One-sample t-test example, in R
Sections 7.1-7.5
Two- and paired-sample hypothesis tests
Two-sample t-test examples, in R
Two-sample t-test spreadsheet example w/m&m data
Two-sample t-test example w/m&m data, in R
Paired-sample t-test example, in R
Variance test example, in R
Sections 8.1-8.3, 8.5; 9.1, 9.2
Parametric vs. nonparametric tests
Mann-Whitney Two-sample test example, in R
Wilcoxon paired-sample test example, in R
Sections 8.9, 8.10, 9.5
Statistical Power Sections 7.6, 8.4, 9.3

Analysis of Variance
Single-factor ANOVA
single-factor ANOVA example, in R
Multiple comparison test
Nonparametric ANOVA
Two-factor ANOVA


Sections 10.1 - 10.3, 10.6
Sections 11.1 - 11.3
Section 10.4
Sections 12.1-12.3, 12.6, 12.7
Goodness of fit
Chi-squared goodness of fit test example, in R
Kolmogorov-Smirnov goodness of fit test example, in R
Contingency tests
Sections 22.1 - 22.5, 22.7 - 22.9
Sections 23.1 - 23.7
Simple Linear Regression and Correlation
Simple linear regression
Regression worksheet
Simple linear correlation
Data transformations

Ch. 17, Sections 18.1 - 18.3
Sections 19.1 - 19.6
Ch. 13
Evaluating Multiple Hypotheses
Akaike's Information Criterion
Multimodel Inference
Model selection example
Model selection example, in R
Model selection: tidepool example, in R
Anderson et al. 2000. JWM64:912-923.
A&B 2002. JWM66:912-918.
Burnham & Anderson 2002. ch.8
Likelihood Methods
Further reading:
Hobbs NT, Hilborn R. 2006. Alternatives to statistical hypothesis testing in ecology: a guide to self teaching. Ecological Applications 16(1):5-19.
Readings TBA

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Homework Assignments
Assignments are due at noon on the date listed.

Assignment

Due Date

One Jan. 16
Two Jan. 23
Study for exam 1
Three
Feb. 6
Four Feb. 13
Study for exam 2
Five Feb. 27
Six March 6

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