Walter W. Piegorsch
Analyzing Environmental Data is based on a course which the author has taught for many years, and prepares students for careers in environmental analysis centered on statistics and allied quantitative methods of evaluation.
Analyzing Environmental Data extends beyond the introductory level, allowing students and environmental science practitioners to develop the expertise to design and perform sophisticated environmental data analyses.
Contents
- Linear regression
- Simple linear regression
- Multiple linear regression
- Qualitative predictors: ANOVA and ANCOVA models
- Random-effects models
- Polynomial regression
- Nonlinear regression
- Estimation and testing
- Piecewise regression models
- Exponential regression models
- Growth curves
- Rational polynomials
- Multiple nonlinear regression
- Generalized linear models
- Generalizing the classical linear model
- Theory of generalized linear models
- Specific forms of generalized linear models
- Quantitative risk assessment with stimulus-response data
- Potency estimation for stimulus-response data
- Risk estimation
- Benchmark analysis
- Uncertainty analysis
- Sensitivity analysis
- Additional topics
- Temporal data and autoregressive modeling
- Time series
- Harmonic regression
- Autocorrelation
- Autocorrelated regression models
- Simple trend and intervention analysis
- Growth curves revisited
- Spatially correlated data
- Spatial correlation
- Spatial point patterns and complete spatial randomness
- Spatial measurement
- Spatial prediction
- Combining environmental information
- Combining P-values
- Effect size estimation
- Meta-analysis
- Historical control information
- Fundamentals of environmental sampling
- Sampling populations - simple random sampling
- Designs to extend simple random sampling
- Specialized techniques for environmental sampling
- Review of probability and statistical inference
- Probability functions
- Families of distributions
- Random sampling
- Parameter estimation
- Statistical inference
- The delta method
Index
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