A Primer of Ecological Statistics, Second Edition explains fundamental material in probability theory, experimental design, and parameter estimation for ecologists and environmental scientists. The book emphasizes a general introduction to probability theory and provides a detailed discussion of specific designs and analyses that are typically encountered in ecology and environmental science. Appropriate for use as either a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design, the Primer also serves as a resource for environmental professionals who need to use and interpret statistics daily but have little or no formal training in the subject.
The book is divided into four parts. Part I discusses the fundamentals of probability and statistical thinking. It introduces the logic and language of probability (Chapter 1), explains common statistical distributions used in ecology (Chapter 2) and important measures of central tendency and spread (Chapter 3), explains P-values, hypothesis testing, and statistical errors (Chapter 4), and introduces frequentist, Bayesian, and Monte Carlo methods of analysis (Chapter 5).
Part II discusses how to successfully design and execute field experiments and sampling studies. Topics include design strategies (Chapter 6), a 'bestiary' of experimental designs (Chapter 7), and transformations and data management (Chapter 8).
Part III discusses specific analyses, and covers the material that is the main core of most statistics texts. Topics include regression (Chapter 9), analysis of variance (Chapter 10), categorical data analysis (Chapter 11), and multivariate analysis (Chapter 12).
Part IV—new to this edition—discusses two central topics in estimating important ecological metrics. Topics include quantification of biological diversity (Chapter 13) and estimating occupancy, detection probability, and population sizes from marked and unmarked populations (Chapter 14).
The book includes a comprehensive glossary, a mathematical appendix on matrix algebra, and extensively annotated tables and figures. Footnotes introduce advanced and ancillary material: some are purely historical, others cover mathematical/statistical proofs or details, and still others address current topics in the ecological literature.
Data files and code used for some of the examples, as well as errata, are available online.
PART I: FUNDAMENTALS OF PROBABILITY AND STATISTICAL THINKING
Probability: An Introduction
Random Variables and Probability Distributions
Summary Statistics: Measures of Location and Spread
Framing and Testing Hypotheses
Three Frameworks for Statistical Inference
PART II: DESIGNING EXPERIMENTS
Designing Successful Field Studies
A Bestiary of Experimental and Sampling Designs
Managing and Curating Data
PART III: DATA ANALYSIS
The Analysis of Variance
The Analysis of Categorical Data
The Analysis of Multivariate Data
PART IV: ESTIMATION
The Measurement of Biodiversity
Detecting Populations and Estimating their Size