Probability Theory is a classic topic in any course of exact sciences, that evolved from the amalgamation of different areas of mathematics, including set and measure theory. An axiomatic treatment of probability is presented in the book. Probability Theory is fundamental to several areas of knowledge, including engineering, computer science, mathematics, physics, sciences, economics, biology, medicine, social sciences and social communication. The book targets graduate students who may not have taken basic courses in these specific topics, and can provide a quick and concise way to obtain the knowledge they need to succeed in advanced courses.
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Praise for the First Edition
“. . . a readable, comprehensive volume that . . . belongs on the desk, close at hand, of any serious researcher or practitioner.” —Mathematical Geosciences
The state of the art in geostatistics
Geostatistical models and techniques such as kriging and stochastic multi-realizations exploit spatial correlations to evaluate natural resources, help optimize their development, and address environmental issues related to air and water quality, soil pollution, and forestry. Geostatistics: Modeling Spatial Uncertainty, Second Edition presents a comprehensive, up-to-date reference on the topic, now featuring the latest developments in the field.
The authors explain both the theory and applications of geostatistics through a unified treatment that emphasizes methodology. Key topics that are the foundation of geostatistics are explored in-depth, including stationary and nonstationary models; linear and nonlinear methods; change of support; multivariate approaches; and conditional simulations. The Second Edition highlights the growing number of applications of geostatistical methods and discusses three key areas of growth in the field:
- New results and methods, including kriging very large datasets; kriging with outliers; nonse??parable space-time covariances; multipoint simulations; pluri-gaussian simulations; gradual deformation; and extreme value geostatistics
- Newly formed connections between geostatistics and other approaches such as radial basis functions, Gaussian Markov random fields, and data assimilation
- New perspectives on topics such as collocated cokriging, kriging with an external drift, discrete Gaussian change-of-support models, and simulation algorithms
Geostatistics, Second Edition is an excellent book for courses on the topic at the graduate level. It also serves as an invaluable reference for earth scientists, mining and petroleum engineers, geophysicists, and environmental statisticians who collect and analyze data in their everyday work.
From the Back Cover
A novel, practical approach to modeling spatial uncertainty.
This book deals with statistical models used to describe natural variables distributed in space or in time and space. It takes a practical, unified approach to geostatistics-integrating statistical data with physical equations and geological concepts while stressing the importance of an objective description based on empirical evidence. This unique approach facilitates realistic modeling that accounts for the complexity of natural phenomena and helps solve economic and development problems-in mining, oil exploration, environmental engineering, and other real-world situations involving spatial uncertainty.
Up-to-date, comprehensive, and well-written, Geostatistics: Modeling Spatial Uncertainty explains both theory and applications, covers many useful topics, and offers a wealth of new insights for nonstatisticians and seasoned professionals alike. This volume:
* Reviews the most up-to-date geostatistical methods and the types of problems they address.
* Emphasizes the statistical methodologies employed in spatial estimation.
* Presents simulation techniques and digital models of uncertainty.
* Features more than 150 figures and many concrete examples throughout the text.
* Includes extensive footnoting as well as a thorough bibliography.
Geostatistics: Modeling Spatial Uncertainty is the only geostatistical book to address a broad audience in both industry and academia. An invaluable resource for geostatisticians, physicists, mining engineers, and earth science professionals such as petroleum geologists, geophysicists, and hydrogeologists, it is also an excellent supplementary text for graduate-level courses in related subjects. –This text refers to an out of print or unavailable edition of this title.
Introducing the concepts and methods of modern statistics with an emphasis on computer assisted data analysis, the book focuses on interpretation of results rather than their computation. Review of probability, collecting data, summarizing and exploring data, sampling distributions of statistics, basic concepts of inference, linear regression and correlation, analysis of single factor and multifactor Experiments.
This book is a new type of intermediate microeconomics textbook.Previously, the choice was between books that use calculus to present formal theory dryly and with few, if any, applications to the real world and books that include applications but present theory using algebra and graphs only. This book uses calculus, algebra, and theory to analyze real-world problems. My purpose is to show that economic theory has practical, problem-solving uses and is not an empty academic exercise.
This book shows how individuals, policymakers, and firms use microeconomic tools to analyze and resolve problems. For examples, students learn that:
- individuals can draw on microeconomic theories when deciding whether to invest and whether to sign a contract that pegs prices to the government’s measure of inflation;
- policymakers (and voters) can employ microeconomics to predict the impact of taxes, regulations, and other measures before they are enacted;
- lawyers and judges use microeconomics in antitrust, discrimination, and contract cases; and
- firms apply microeconomic principles to produce at least cost and maximize profit, select strategies, decide whether to buy from a market or to produce internally, and write contracts to provide optimal incentives for employees.
My experience in teaching microeconomics for the departments of economics at the Massachusetts Institute of Technology; the University of Pennsylvania; the University of California, Berkeley; and the Wharton Business School has convinced me that students prefer the emphasis on real-world issues.