Statistics for Earth and Environmental Scientists 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Statistics for Earth and Environmental Scientists

简体网页||繁体网页
John Schuenemeyer 作者
Wiley-Blackwell
译者
2011-1-4 出版日期
384 页数
GBP 110.00 价格
Hardcover
丛书系列
9780470584699 图书编码

Statistics for Earth and Environmental Scientists 在线电子书 图书标签: 统计  地球科学  环境科学   


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发表于2024-11-26


Statistics for Earth and Environmental Scientists 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Statistics for Earth and Environmental Scientists 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Statistics for Earth and Environmental Scientists 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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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.

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