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Details for: Environmental and ecological statistics with R
Environmental and ecological statistics with R
By: Qian, Song S
Material type: TextSeries: Chapman and Hall/CRC Press Applied Environmental StatisticsPublisher: Boca Raton CRC Press 2017Edition: 2ndDescription: xxiii, 535 p.ISBN: 9781498728720Subject(s): Environmental sciences - statistical methods | Ecology - statistical methods | R - Computer program language | Big Data DDC classification: 550.2855133 Summary: Emphasizing the inductive nature of statistical thinking, Environmental and Ecological Statistics with R, Second Edition, connects applied statistics to the environmental and ecological fields. Using examples from published works in the ecological and environmental literature, the book explains the approach to solving a statistical problem, covering model specification, parameter estimation, and model evaluation. It includes many examples to illustrate the statistical methods and presents R code for their implementation. The emphasis is on model interpretation and assessment, and using several core examples throughout the book, the author illustrates the iterative nature of statistical inference. The book starts with a description of commonly used statistical assumptions and exploratory data analysis tools for the verification of these assumptions. It then focuses on the process of building suitable statistical models, including linear and nonlinear models, classification and regression trees, generalized linear models, and multilevel models. It also discusses the use of simulation for model checking, and provides tools for a critical assessment of the developed models. The second edition also includes a complete critique of a threshold model. Environmental and Ecological Statistics with R, Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers through the process of scientific problem solving and statistical model development, it eases the transition from scientific hypothesis to statistical model. https://www.crcpress.com/Environmental-and-Ecological-Statistics-with-R-Second-Edition/Qian/p/book/9781498728720
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550 V2P7 Prehistoric river Saraswati, Western India: geological appraisal and social aspects 550.15118 G7I6 Introduction to environmental modeling 550.1515357 S3G5 Global optimization methods in geophysical inversion 550.2855133 Q4E6 Environmental and ecological statistics with R 551.015195 M6S7 Spatial and spatio-temporal geostatistical modeling and kriging 551.447 M2U6 Underland: a deep time journey 551.464 B6T4 Tides: a very short introduction
Emphasizing the inductive nature of statistical thinking, Environmental and Ecological Statistics with R, Second Edition, connects applied statistics to the environmental and ecological fields. Using examples from published works in the ecological and environmental literature, the book explains the approach to solving a statistical problem, covering model specification, parameter estimation, and model evaluation. It includes many examples to illustrate the statistical methods and presents R code for their implementation. The emphasis is on model interpretation and assessment, and using several core examples throughout the book, the author illustrates the iterative nature of statistical inference.
The book starts with a description of commonly used statistical assumptions and exploratory data analysis tools for the verification of these assumptions. It then focuses on the process of building suitable statistical models, including linear and nonlinear models, classification and regression trees, generalized linear models, and multilevel models. It also discusses the use of simulation for model checking, and provides tools for a critical assessment of the developed models. The second edition also includes a complete critique of a threshold model.
Environmental and Ecological Statistics with R, Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers through the process of scientific problem solving and statistical model development, it eases the transition from scientific hypothesis to statistical model.
https://www.crcpress.com/Environmental-and-Ecological-Statistics-with-R-Second-Edition/Qian/p/book/9781498728720
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