Environmental and Ecological Statistics with R Book

BASIC CONCEPTS
Introduction
The Everglades Example Statistical Issues
R
What Is R?
Getting Started with R The R Commander
Statistical Assumptions
The Normality Assumption The Independence Assumption The Constant Variance Assumption Exploratory Data Analysis From Graphs to Statistical Thinking
Statistical Inference
Estimation of Population Mean and Confidence Interval Hypothesis Testing A General Procedure Nonparametric Methods for Hypothesis Testing Significance Level alpha, Power 1 - beta, and p-Value One-Way Analysis of Variance Examples
STATISTICAL MODELING
Linear Models
ANOVA as a Linear Model Simple and Multiple Linear Regression Models General Considerations in Building a Predictive Model Uncertainty in Model Predictions Two-Way ANOVA
Nonlinear Models
Nonlinear Regression Smoothing Smoothing and Additive Models
Classification and Regression Tree
The Willamette River Example Statistical Methods Comments
Generalized Linear Model
Logistic Regression Model Interpretation Diagnostics Seed Predation by Rodents: A Second Example of Logistic Regression Poisson Regression Model Generalized Additive Models
ADVANCED STATISTICAL MODELING
Simulation for Model Checking and Statistical Inference
Simulation Summarizing Linear and Nonlinear Regression Using Simulation Simulation Based on Resampling
Multilevel Regression
Multilevel Structure and Exchangeability Multilevel ANOVA Multilevel Linear Regression Generalized Multilevel Models
References
Index