Probability And Statistics Applications For Environmental Science
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Author | : Stacey J Shaefer |
Publisher | : CRC Press |
Total Pages | : 394 |
Release | : 2007-02-22 |
Genre | : Mathematics |
ISBN | : 1000654060 |
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 ap
Author | : Stacey J Shaefer |
Publisher | : CRC Press |
Total Pages | : 394 |
Release | : 2007-02-22 |
Genre | : Mathematics |
ISBN | : 0849375614 |
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.
Author | : Miguel F. Acevedo |
Publisher | : CRC Press |
Total Pages | : 549 |
Release | : 2012-12-07 |
Genre | : Mathematics |
ISBN | : 1466592214 |
Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustain
Author | : Louis Theodore |
Publisher | : CRC Press |
Total Pages | : 390 |
Release | : 2015-09-25 |
Genre | : Mathematics |
ISBN | : 1498714404 |
A Training Tool for the Environmental Risk ProfessionalEnvironmental Risk Analysis: Probability Distribution Calculations defines the role that probability distributions play in risk analysis, and gives direction on how to measure and compare the magnitude of risk more efficiently. Designed for the practicing environmental engineer and scientist, t
Author | : Vic Barnett |
Publisher | : John Wiley & Sons |
Total Pages | : 316 |
Release | : 2005-12-13 |
Genre | : Mathematics |
ISBN | : 0470026979 |
In modern society, we are ever more aware of the environmental issues we face, whether these relate to global warming, depletion of rivers and oceans, despoliation of forests, pollution of land, poor air quality, environmental health issues, etc. At the most fundamental level it is necessary to monitor what is happening in the environment – collecting data to describe the changing scene. More importantly, it is crucial to formally describe the environment with sound and validated models, and to analyse and interpret the data we obtain in order to take action. Environmental Statistics provides a broad overview of the statistical methodology used in the study of the environment, written in an accessible style by a leading authority on the subject. It serves as both a textbook for students of environmental statistics, as well as a comprehensive source of reference for anyone working in statistical investigation of environmental issues. Provides broad coverage of the methodology used in the statistical investigation of environmental issues. Covers a wide range of key topics, including sampling, methods for extreme data, outliers and robustness, relationship models and methods, time series, spatial analysis, and environmental standards. Includes many detailed practical and worked examples that illustrate the applications of statistical methods in environmental issues. Authored by a leading authority on environmental statistics.
Author | : John H. Schuenemeyer |
Publisher | : John Wiley & Sons |
Total Pages | : 341 |
Release | : 2011-04-12 |
Genre | : Mathematics |
ISBN | : 1118102215 |
A comprehensive treatment of statistical applications for solving real-world environmental problems A host of complex problems face today's earth science community, such as evaluating the supply of remaining non-renewable energy resources, assessing the impact of people on the environment, understanding climate change, and managing the use of water. Proper collection and analysis of data using statistical techniques contributes significantly toward the solution of these problems. Statistics for Earth and Environmental Scientists presents important statistical concepts through data analytic tools and shows readers how to apply them to real-world problems. The authors present several different statistical approaches to the environmental sciences, including Bayesian and nonparametric methodologies. The book begins with an introduction to types of data, evaluation of data, modeling and estimation, random variation, and sampling—all of which are explored through case studies that use real data from earth science applications. Subsequent chapters focus on principles of modeling and the key methods and techniques for analyzing scientific data, including: Interval estimation and Methods for analyzinghypothesis testing of means time series data Spatial statistics Multivariate analysis Discrete distributions Experimental design Most statistical models are introduced by concept and application, given as equations, and then accompanied by heuristic justification rather than a formal proof. Data analysis, model building, and statistical inference are stressed throughout, and readers are encouraged to collect their own data to incorporate into the exercises at the end of each chapter. Most data sets, graphs, and analyses are computed using R, but can be worked with using any statistical computing software. A related website features additional data sets, answers to selected exercises, and R code for the book's examples. Statistics for Earth and Environmental Scientists is an excellent book for courses on quantitative methods in geology, geography, natural resources, and environmental sciences at the upper-undergraduate and graduate levels. It is also a valuable reference for earth scientists, geologists, hydrologists, and environmental statisticians who collect and analyze data in their everyday work.
Author | : Timothy DelSole |
Publisher | : Cambridge University Press |
Total Pages | : 545 |
Release | : 2022-02-24 |
Genre | : Mathematics |
ISBN | : 1108472419 |
An accessible introduction to statistical methods for students in the climate sciences.
Author | : Steven P. Millard |
Publisher | : Springer Science & Business Media |
Total Pages | : 305 |
Release | : 2013-10-16 |
Genre | : Computers |
ISBN | : 1461484561 |
This book describes EnvStats, a new comprehensive R package for environmental statistics and the successor to the S-PLUS module EnvironmentalStats for S-PLUS (first released in 1997). EnvStats and R provide an open-source set of powerful functions for performing graphical and statistical analyses of environmental data, bringing major environmental statistical methods found in the literature and regulatory guidance documents into one statistical package, along with an extensive hypertext help system that explains what these methods do, how to use these methods, and where to find them in the environmental statistics literature. EnvStats also includes numerous built-in data sets from regulatory guidance documents and the environmental statistics literature. This book shows how to use EnvStats and R to easily: * graphically display environmental data * plot probability distributions * estimate distribution parameters and construct confidence intervals on the original scale for commonly used distributions such as the lognormal and gamma, as well as do this nonparametrically * estimate and construct confidence intervals for distribution percentiles or do this nonparametrically (e.g., to compare to an environmental protection standard) * perform and plot the results of goodness-of-fit tests * compute optimal Box-Cox data transformations * compute prediction limits and simultaneous prediction limits (e.g., to assess compliance at multiple sites for multiple constituents) * perform nonparametric estimation and test for seasonal trend (even in the presence of correlated observations) * perform power and sample size computations and create companion plots for sampling designs based on confidence intervals, hypothesis tests, prediction intervals, and tolerance intervals * deal with non-detect (censored) data * perform Monte Carlo simulation and probabilistic risk assessment * reproduce specific examples in EPA guidance documents EnvStats combined with other R packages (e.g., for spatial analysis) provides the environmental scientist, statistician, researcher, and technician with tools to “get the job done!”
Author | : Bhisham C. Gupta |
Publisher | : John Wiley & Sons |
Total Pages | : 896 |
Release | : 2013-04-29 |
Genre | : Mathematics |
ISBN | : 1118464044 |
Introducing the tools of statistics and probability from the ground up An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences. Unique among books of this kind, Statistics and Probability with Applications for Engineers and Scientists covers descriptive statistics first, then goes on to discuss the fundamentals of probability theory. Along with case studies, examples, and real-world data sets, the book incorporates clear instructions on how to use the statistical packages Minitab® and Microsoft® Office Excel® to analyze various data sets. The book also features: • Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and process capability indices • A clear presentation of nonparametric methods and simple and multiple linear regression methods, as well as a brief discussion on logistic regression method • Comprehensive guidance on the design of experiments, including randomized block designs, one- and two-way layout designs, Latin square designs, random effects and mixed effects models, factorial and fractional factorial designs, and response surface methodology • A companion website containing data sets for Minitab and Microsoft Office Excel, as well as JMP ® routines and results Assuming no background in probability and statistics, Statistics and Probability with Applications for Engineers and Scientists features a unique, yet tried-and-true, approach that is ideal for all undergraduate students as well as statistical practitioners who analyze and illustrate real-world data in engineering and the natural sciences.
Author | : Wayne R. Ott |
Publisher | : Routledge |
Total Pages | : 336 |
Release | : 2018-12-13 |
Genre | : Mathematics |
ISBN | : 1351450077 |
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 importa