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Academic Programs - ESM 206B - STATISTICS & DATA ANALYSIS FOR ENVIRONMENTAL SCIENCE AND MANAGEMENT

Develop skills and conceptual framework to effectively use data to solve practical problems. Topics include descriptive statistics, hypothesis testing, experimental design, exploratory data analysis, probability and uncertainty, time series analysis, and spatial stats. Emphasis of case studies from environmental problems.

Syllabus

Instructor(s)

 

Bruce Kendall

 

Homeworks

Date Title
4/27/2009 Homework 3 - Solutions
4/24/2009 Cholesterol
4/24/2009 Homework 3
4/21/2009 Logistic Regression - Hwk. 2
4/21/2009 Homework_2 - Solutions
4/16/2009 Homework 2
4/16/2009 Apple data
4/13/2009 Homework 1 - Solutions
4/8/2009 Homework1
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Lab

Date Title
4/28/2009 Bootstrap Data
4/28/2009 diplonychus.csv
4/28/2009 notonecta.csv
4/28/2009 anisops.csv
4/28/2009 Bootstrap Lab
4/21/2009 Fake Crayfish Data
4/21/2009 ANCOVA lab
4/15/2009 Logistic Regression
4/14/2009 Ellison Darlingtonia Data 3
4/14/2009 Logistic Lab
4/8/2009 Stepwise Model Selection for Multiple Regression Lab
4/8/2009 Fake Cyano Data
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Lectures

Date Title
4/29/2009 Intro to Multivariate Analysis & Visualization
4/28/2009 Multivariate Distance and Mantel Tests
4/15/2009 Analysis of Covariance & Review of Random vs. Fized Effects
4/13/2009 Using Regression in Experimental Design
4/8/2009 Logistic Regression
4/6/2009 Model Selection and Introduction to Nonlinear Models
4/1/2009 Introduction to Model Selection
3/30/2009 Review of Multiple Regression
Randomization Intro
Bootstrapping
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Links

Date Title
4/27/2009 Crowley Introduction to Monte Carlo and Bootstrapping
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Resources

Date Title
4/15/2009 More Notes on Efficient Data Management
4/13/2009 Cottingham et al (2005) Knowing when to draw the line: designing more informative ecological experiments
4/8/2009 Guidelines for Effective Data Management