Environmental And Ecological Statistics With R 2Nd Edn by Song S. Qian, Taylor & Francis

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Taylor & Francis Environmental And Ecological Statistics With R 2Nd Edn by Song S. Qian

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._x000D__x000D__x000D_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. _x000D__x000D__x000D_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._x000D_ _x000D_ I Basic Concepts _x000D_ _x000D_ _x000D_ Introduction_x000D_ _x000D_ _x000D_ A Crash Course on R_x000D_ _x000D_ _x000D_ Statistical Assumptions_x000D_ _x000D_ _x000D_ Statistical Inference_x000D_ _x000D_ _x000D_ II Statistical Modeling_x000D_ _x000D_ _x000D_ Linear Models_x000D_ _x000D_ _x000D_ Nonlinear Models_x000D_ _x000D_ _x000D_ Classi cation and Regression Tree_x000D_ _x000D_ _x000D_ Generalized Linear Model_x000D_ _x000D_ _x000D_ III Advanced Statistical Modeling_x000D_ _x000D_ _x000D_ Simulation for Model Checking and Statistical Inference_x000D_ _x000D_ _x000D_ Multilevel Regression_x000D_ _x000D_ _x000D_ Using Simulation for Evaluating Models Based on Statistical Signicance Testing_x000D_ _x000D_ _x000D_ Bibliography_x000D_