Qian Environmental and Ecological Statistics with R

Erscheinungsjahr 2011
ISBN: 978-1-4200-6208-3
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: 0 - No protection

E-Book, Englisch, 440 Seiten

Reihe: Chapman & Hall/CRC Applied Environmental Statistics

Emphasizing the inductive nature of statistical thinking, Environmental and Ecological Statistics with R connects applied statistics to the environmental and ecological fields. It follows the general approach to solving a statistical modeling problem, covering model specification, parameter estimation, and model evaluation. The author uses many examples to illustrate the statistical models and presents R implementations of the models.

The book first builds a foundation for conducting a simple data analysis task, such as exploratory data analysis and fitting linear regression models. It then focuses on statistical modeling, including linear and nonlinear models, classification and regression tree, and the generalized linear model. The text also discusses the use of simulation for model checking, provides tools for a critical assessment of the developed model, and explores multilevel regression models, which are a class of models that can have a broad impact in environmental and ecological data analysis.

Based on courses taught by the author at Duke University, this book focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers through the processes of scientific problem solving and statistical model development, it eases the transition from scientific hypothesis to statistical model.

Zielgruppe

Graduate students, researchers, and practitioners in environmental science and ecology.

Autoren/Hrsg.

Qian, Song S.

Fachgebiete

• Geowissenschaften Umweltwissenschaften Umwelttechnik
• Mathematik | Informatik Mathematik Stochastik
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
• Geowissenschaften Geographie | Raumplanung Geographie: Sachbuch, Reise
• Naturwissenschaften Biowissenschaften Biowissenschaften Ökologie
• Naturwissenschaften Biowissenschaften Biowissenschaften Biowissenschaften, Biologie: Sachbuch, Naturführer

Inhaltsverzeichnis

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

Über Autor(innen)

Song S. Qian is an associate research professor in the Nicholas School of the Environment at Duke University. Dr. Qian’s research consists of adaptive management strategies for watershed TMDL, GIS-assisted watershed modeling, water quality assessments, modeling marine mammal habitats, environmental sampling design, and more.