Statistics for Environmental Science and

Revised, expanded, and updated, this second edition of Statistics for Environmental Science and Management is that rare animal, a resource that works well as a text for graduate courses and a reference for appropriate statistical approaches to specific environmental problems. It is uncommon to find so many important environmental topics covered in one book. Its strength is author Bryan Manly's ability to take a non-mathematical approach while keeping essential mathematical concepts intact. He clearly explains statistics without dwelling on heavy mathematical development.The book begins by describing the important role statistics play in environmental science. It focuses on how to collect data, highlighting the importance of sampling and experimental design in conducting rigorous science. It presents a variety of key topics specifically related to environmental science such as monitoring, impact assessment, risk assessment, correlated and censored data analysis, to name just a few.Revised, updated or expanded material on:Data Quality Objectives Generalized Linear Models Spatial Data Analysis Censored Data Monte Carlo Risk AssessmentThere are numerous books on environmental statistics; however, while some focus on multivariate methods and others on the basic components of probability distributions and how they can be used for modeling phenomenon, most do not include the material on sampling and experimental design that this one does. It is the variety of coverage, not sacrificing too much depth for breadth, that sets this book apart.

Preface to the Second Edition	p. xi
Preface to the First Edition	p. xiii
The Role of Statistics in Environmental Science	p. 1
Introduction	p. 1
Some Examples	p. 1
The Importance of Statistics in the Examples	p. 19
Chapter Summary	p. 19
Exercises	p. 20
Environmental Sampling	p. 23
Introduction	p. 23
Simple Random Sampling	p. 24
Estimation of Population Means	p. 24
Estimation of Population Totals	p. 29
Estimation of Proportions	p. 30
Sampling and Nonsampling Errors	p. 32
Stratified Random Sampling	p. 33
Post-Stratification	p. 38
Systematic Sampling	p. 39
Other Design Strategies	p. 44
Ratio Estimation	p. 46
Double Sampling	p. 50
Choosing Sample Sizes	p. 51
Unequal-Probability Sampling	p. 53
The Data Quality Objectives Process	p. 55
Chapter Summary	p. 56
Exercises	p. 58
Models for Data	p. 61
Statistical Models	p. 61
Discrete Statistical Distributions	p. 61
The Hypergeometric Distribution	p. 62
The Binomial Distribution	p. 63
The Poisson Distribution	p. 64
Continuous Statistical Distributions	p. 65
The Exponential Distribution	p. 66
The Normal or Gaussian Distribution	p. 67
The Lognormal Distribution	p. 67
The Linear Regression Model	p. 68
Factorial Analysis of Variance	p. 74
One-Factor Analysis of Variance	p. 76
Two-Factor Analysis of Variance	p. 76
Three-Factor Analysis of Variance	p. 78
Repeated-Measures Designs	p. 82
Multiple Comparisons and Contrasts	p. 83
Generalized Linear Models	p. 84
Chapter Summary	p. 90
Exercises	p. 91
Drawing Conclusions from Data	p. 97
Introduction	p. 97
Observational and Experimental Studies	p. 97
True Experiments and Quasi-Experiments	p. 99
Design-Based and Model-Based Inference	p. 101
Tests of Significance and Confidence Intervals	p. 103
Randomization Tests	p. 105
Bootstrapping	p. 108
Pseudoreplication	p. 110
Multiple Testing	p. 112
Meta-Analysis	p. 114
Bayesian Inference	p. 119
Chapter Summary	p. 120
Exercises	p. 122
Environmental Monitoring	p. 125
Introduction	p. 125
Purposely Chosen Monitoring Sites	p. 126
Two Special Monitoring Designs	p. 126
Designs Based on Optimization	p. 129
Monitoring Designs Typically Used	p. 129
Detection of Changes by Analysis of Variance	p. 131
Detection of Changes Using Control Charts	p. 133
Detection of Changes Using CUSUM Charts	p. 140
Chi-Squared Tests for a Change in a Distribution	p. 145
Chapter Summary	p. 149
Exercises	p. 150
Impact Assessment	p. 153
Introduction	p. 153
The Simple Difference Analysis with BACI Designs	p. 155
Matched Pairs with a BACI Design	p. 158
Impact-Control Designs	p. 161
Before-After Designs	p. 162
Impact-Gradient Designs	p. 163
Inferences from Impact Assessment Studies	p. 163
Chapter Summary	p. 164
Exercises	p. 165
Assessing Site Reclamation	p. 167
Introduction	p. 167
Problems with Tests of Significance	p. 167
The Concept of Bioequivalence	p. 168
Two-Sided Tests of Bioequivalence	p. 171
Chapter Summary	p. 176
Exercises	p. 177
Time Series Analysis	p. 179
Introduction	p. 179
Components of Time Series	p. 180
Serial Correlation	p. 182
Tests for Randomness	p. 186
Detection of Change Points and Trends	p. 190
More-Complicated Time Series Models	p. 194
Frequency Domain Analysis	p. 201
Forecasting	p. 202
Chapter Summary	p. 203
Exercises	p. 204
Spatial-Data Analysis	p. 207
Introduction	p. 207
Types of Spatial Data	p. 207
Spatial Patterns in Quadrat Counts	p. 211
Correlation between Quadrat Counts	p. 217
Randomness of Point Patterns	p. 219
Correlation between Point Patterns	p. 221
Mantel Tests for Autocorrelation	p. 222
The Variogram	p. 224
Kriging	p. 228
Correlation between Variables in Space	p. 230
Chapter Summary	p. 231
Exercises	p. 233
Censored Data	p. 237
Introduction	p. 237
Single Sample Estimation	p. 237
Estimation of Quantiles	p. 244
Comparing the Means of Two or More Samples	p. 244
Regression with Censored Data	p. 247
Chapter Summary	p. 247
Exercises	p. 248
Monte Carlo Risk Assessment	p. 249
Introduction	p. 249
Principles for Monte Carlo Risk Assessment	p. 250
Risk Analysis Using a Spreadsheet	p. 251
Chapter Summary	p. 253
Exercises	p. 253
Final Remarks	p. 255
Appendices	p. 257
References	p. 279
Index	p. 291
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Statistics for Environmental Science and Management, Second Edition

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