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Statistical Computation for Environmental Sciences in R

complexity, environmental scientists are struggling to understand and exploit powerful new statistical tools for making sense of ecological processes;

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Models for Ecological Data

complexity, environmental scientists are struggling to understand and exploit powerful new statistical tools for making sense of ecological processes;

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Biometry for Forestry and Environmental Data

Biometry for Forestry and Environmental Data with Examples in R focuses on statistical methods that are widely applicable in forestry and;

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Statistical Data Analysis Explained

of statistical concepts and carries readers forward to a deeper and more extensive understanding of the use of statistics in environmental sciences. The;

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Statistics in Environmental Sciences

Statistical tools are indispensable for the environmental sciences. They have become an integral part of the scientific process, from the;

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Recent Developments in Mathematical, Statistical and Computational Sciences

of research fields, including medicine, health sciences, biology, environmental science, engineering, physics, chemistry, computation, finance;

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Applied Statistics for Environmental Science with R

Applied Statistics for Environmental Science with R presents the theory and application of statistical techniques in environmental;

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Statistical Methods for Groundwater Monitoring

A new edition of the most comprehensive overview of statistical methods for environmental monitoring applications Thoroughly updated to;

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Statistical Methods for the Environmental Sciences

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The R Student Companion

for statistical analysis, The R Student Companion approaches R more completely as a comprehensive tool for scientific computing and graphing.;

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The R Student Companion

for statistical analysis, The R Student Companion approaches R more completely as a comprehensive tool for scientific computing and graphing.;

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Statistics for Earth and Environmental Scientists

A comprehensive treatment of statistical applications for solving real-world environmental problems A host of complex problems face today's;

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Recent Advances in Mathematical and Statistical Methods

in mathematical and statistical modelling that have been developed for a wide range of research fields, including medical, health sciences, biology;

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Nonparametric Statistical Methods Using R

nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the;

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Nonparametric Statistical Methods Using R

general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation;

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Environmental and Ecological Statistics with R

Ecological Statistics with R, Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding;

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Environmental and Ecological Statistics with R

Statistics with R, Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers;

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Applied Univariate, Bivariate, & Multivariate Stat istics

and R contains an accessible introduction to statistical modeling techniques commonly used in the social and natural sciences. The text offers;

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Modeling Language, Cognition And Action - Proceedings Of The Ninth Neural Computation And Psychology Workshop

selected for coverage in:* Neuroscience Citation Index (R)* Index to Scientific & Technical Proceedings (R) (ISTP (R) / ISI Proceedings)* Index to;

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Statistics Using R

sciences, engineering, management and so on. The book introduces statistical terminology and defines it for the benefit of a novice. For a;

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Statistics And Data With R

R, an Open Source software, has become the de facto statistical computing environment. It has an excellent collection of data;

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Spatio-Temporal Heterogeneity

confounded by environmental heterogeneity. Spatio-Temporal Heterogeneity explores a range of available statistical methods to help ecologists in the;

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Analysis Biomarker Data Practical Guide

A how to guide for applying statistical methods to biomarker data analysis Presenting a solid foundation for the statistical methods;

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Numerical Issues In Statistical Computing For The Social Scientist

on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social;

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Expect the Unexpected

odd-numbered problems. Several sections of this edition are accompanied by instructions using the programming language R for statistical;

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Using R for Data Analysis in Social Sciences

Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for;

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Multivariate Statistical Methods

edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used;

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