Probability And Statistics Applications for Environmental Science

Simple, clear, and to the point, Probability and Statistics Applications for Environmental Science delineates the fundamentals of statistics, imparting a basic understanding of the theory and mechanics of the calculations. User-friendliness, uncomplicated explanations, and coverage of example applications in the environmental field set this book apart from other textbooks on the same subject.Striking a balance between theory and applied mathematics, the material is divided into three parts. Part I sets the stage with coverage of principles and fundamentals, such as set notation, probability distributions, and the estimation of the mean and variance. Part II discusses traditional statistics applications, centering around the uses of probability distributions, including how they relate to reliability and failure theory. The authors elucidate many of the important distributions, Monte Carlo methods, and fault and event trees. Part III delves into what some have come to define as contemporary statistics. It covers hypothesis testing, Student's t and chi-square tests, regression analysis, analysis of variance (ANOVA), and nonparametric tests. The book's coverage is thorough, its presentation logical and geared to student's needs. It includes problems and solutions within the text and tables, a glossary of terms, and an introduction to design of experiments in the appendices. The authors, known for their meticulously accurate, articulate, and practical writing style, master the difficult task of explaining very complicated subject matter in a way that is easily understood. The book features a clear, concise presentation that makes both teaching and learning easier.

FUNDAMENTALSPAC. Permutations and CombinationsPDI. Probability Definitions and Interpretations SNE. Set Notation BTH. Basic TheoremsCOP. Conditional ProbabilityRAR. Random Variables and Random NumbersPDF. Introduction to Probability DistributionsEXV. Expected ValuesEMV. Estimation of Mean and VarianceTRADITIONAL APPLICATIONSBAY. Bayes' Theorem SPS. Series and Parallel SystemsBIN. The Binomial DistributionREL. Reliability Relations HYP. Hypergeometric Distribution POI. Poisson DistributionEXP. Exponential Distribution WBL. Weibull Distribution NOR. Normal DistributionLOG. Log-Normal DistributionMON. Monte Carlo Simulation FET. Fault Tree and Event Tree Analysis CONTEMPORARY APPLICATIONSCIM. Confidence Intervals for MeansCIP. Confidence Intervals for Proportions HYT. Hypothesis Testing TMP. Hypothesis Test for Means and ProportionsCHI. Chi-Square Distribution FFF. The F Distribution REG. Regression Analysis: Method of Least Squares NPT. Nonparametric Tests ANV. Analysis of VarianceAppendix A: Statistics Tables Appendix B: Glossary of TermsAppendix C: Introduction to Design of Experiments Index