The Role of Statistics in Environmental Science
Introduction
Some Examples
The Importance of Statistics in the Examples
Chapter Summary
Exercises
Environmental Sampling
Introduction
Simple Random Sampling
Estimation of Population Means
Estimation of Population Totals
Estimation of Proportions
Sampling and Nonsampling Errors
Stratified Random Sampling
Post-Stratification
Systematic Sampling
Other Design Strategies
Ratio Estimation
Double Sampling0
Choosing Sample Sizes1
Unequal-Probability Sampling
The Data Quality Objectives Process
Chapter Summary
Exercises
Models for Data
Statistical Models
Discrete Statistical Distributions
Continuous Statistical Distributions
The Linear Regression Model8
Factorial Analysis of Variance
Generalized Linear Models
Chapter Summary
Exercises
Drawing Conclusions from Data
Introduction
Observational and Experimental Studies
True Experiments and Quasi-Experiments
Design-Based and Model-Based Inference
Tests of Significance and Confidence Intervals
Randomization Tests
Bootstrapping
Pseudoreplication
Multiple Testing
Meta-Analysis
Bayesian Inference
Chapter Summary
Exercises
Environmental Monitoring
Introduction
Purposely Chosen Monitoring Sites
Two Special Monitoring Designs6
Designs Based on Optimization
Monitoring Designs Typically Used
Detection of Changes by Analysis of Variance
Detection of Changes Using Control Charts
Detection of Changes Using CUSUM Charts
Chi-Squared Tests for a Change in a Distribution
Chapter Summary
Exercises
Impact Assessment
Introduction
The Simple Difference Analysis with BACI Designs
Matched Pairs with a BACI Design.
Impact-Control Designs
Before–After Designs
Impact-Gradient Designs
Inferences from Impact Assessment Studies
Chapter Summary
Exercises
Assessing Site Reclamation
Introduction
Problems with Tests of Significance
The Concept of Bioequivalence
Two-Sided Tests of Bioequivalence
Chapter Summary
Exercises
Time Series Analysis
Introduction
Components of Time Series
Serial Correlation
Tests for Randomness
Detection of Change Points and Trends
More-Complicated Time Series Models
Frequency Domain Analysis
Forecasting
Chapter Summary
Exercises
Spatial-Data Analysis
Introduction
Types of Spatial Data
Spatial Patterns in Quadrat Counts
Correlation between Quadrat Counts
Randomness of Point Patterns
Correlation between Point Patterns
Mantel Tests for Autocorrelation
The Variogram
Kriging
Correlation between Variables in Space
Chapter Summary
Exercises
Censored Data
Introduction
Single Sample Estimation
Estimation of Quantiles
Comparing the Means of Two or More Samples
Regression with Censored Data
Chapter Summary
Exercises
Monte Carlo Risk Assessment
Introduction
Principles for Monte Carlo Risk Assessment
Risk Analysis Using a Spreadsheet
Chapter Summary
Exercises
Final Remarks
Appendices
References
Index
Biography
Bryan F.J. Manly
