Environmental Statistics and Data Analysis

This easy-to-understand introduction emphasizes the areas of probability theory and statistics that are important in environmental monitoring, data analysis, research, environmental field surveys, and environmental decision making. It communicates basic statistical theory with very little abstract mathematical notation, but without omitting important details and assumptions. Topics include Bayes' Theorem, geometric distribution, computer simulation, histograms and frequency plots, maximum likelihood estimation, the tail exponential method, Bernoulli processes, Poisson processes, diffusion and dispersion of pollutants, normal distribution, confidence intervals, and stochastic dilution; gamma, chi-square, and Weibull distributions; and the two- and three-parameter lognormal distributions. The author also presents the Statistical Theory of Rollback, which allows data analysts and regulatory officials to estimate the effect of different emission control strategies on environmental quality frequency distributions. Assuming only a basic knowledge of algebra and calculus, Environmental Statistics and Data Analysis provides an outstanding reference and collection of statistical procedures for analyzing environmental data and making accurate environmental predictions.

Table of Contents:
Random Processes, Stochastic Processes in the Environment, Structure of the Book, Theory of Probability, Probability Concepts, Probability Laws, Conditional Probability and Bayes' Theorem, Summary, Problems, Probability Models, Discrete Probability Models, Continuous Random Variables, Moments, Expected Value, and Central Tendency, Variance, Kurtosis, and Skewness, Analysis of Observed Data, Summary, Problems, Bernoulli Processes, Conditions for Bernoulli Process, Development of Model, Binomial Distribution, Applications to Environmental Problems, Computation of B(n,p), Problems, Poisson Processes, Conditions for Poisson Process, Development of Model, Poisson Distribution, Examples, Applications to Environmental Problems, Computation of P(l,t) , Problems, Diffusion and Dispersion of Pollutants, Wedge Machine, Particle Frame Machine, Plume Model, Summary and Conclusions, Problems, Normal Processes, Conditions for Normal Process, Development of Model, Confidence Intervals, Applications to Environmental Problems, Computation of N(m,s) , Problems, Dilution of Pollutants, Deterministic Dilution, Stochastic Dilution, Applications to Environmental Problems, Summary and Conclusions, Problems, Lognormal Processes, Conditions for Lognormal Process, Development of Model, Lognormal Probability Model, Estimating Parameters of the Lognormal Distribution, Three-Parameter Lognormal Model, Statistical Theory of Rollback, Applications to Environmental Problems, Summary and Conclusions, Problems, Index