Environmental Statistics and Data Analysis [Hardcover]

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.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)
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