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The last fifteen years have seen a surge in the development and use of modern quantitative methods in environmental and ecological data analysis. However, the available literature focus on only a few aspects of the methodology and leave out some of the important ones. This book provides a comprehensive account of both established and new techniques of multivariate data analysis appropriate to the study of environmental and ecological problems. This book is prepared using a recently most popular Programming Language called R, which is an open-source statistical environment. The choice of R for…mehr

Produktbeschreibung
The last fifteen years have seen a surge in the development and use of modern quantitative methods in environmental and ecological data analysis. However, the available literature focus on only a few aspects of the methodology and leave out some of the important ones. This book provides a comprehensive account of both established and new techniques of multivariate data analysis appropriate to the study of environmental and ecological problems. This book is prepared using a recently most popular Programming Language called R, which is an open-source statistical environment. The choice of R for this purpose is influenced by the fact that it is powerful, free and the graphics capability is unparalleled. The book is a result of research, testing and successive refinements of methods and approaches. This comprehensive and flexible treatment of the most important multivariate data analysis techniques will be of great value to graduate students and professional researchers in ecology, agriculture, forestry and environmental management, and to statisticians and mathematicians working with ecological and environmental problems.
Autorenporträt
Zerihun studied Biology for his BSc., Botany for his MSc. in Addis Abba University, Ethiopia and Plant Ecology for his PhD in the Institute of Ecological Botany, Uppsala University, Sweden. He is currently teaching and conducting research on Environment, Landscape Ecology, Multivariate Methods of Data Analysis and Climate Change.