Buch, Englisch, 310 Seiten, Format (B × H): 224 mm x 142 mm, Gewicht: 618 g
Buch, Englisch, 310 Seiten, Format (B × H): 224 mm x 142 mm, Gewicht: 618 g
Reihe: Chapman & Hall/CRC Applied Environmental Statistics
ISBN: 978-1-4200-6147-5
Verlag: Taylor & Francis Ltd
Revised, expanded, and updated, this second edition of Statistics for Environmental Science and Management is that rare animal, a resource that works well as a text for graduate courses and a reference for appropriate statistical approaches to specific environmental problems. It is uncommon to find so many important environmental topics covered in one book. Its strength is author Bryan Manly’s ability to take a non-mathematical approach while keeping essential mathematical concepts intact. He clearly explains statistics without dwelling on heavy mathematical development.
The book begins by describing the important role statistics play in environmental science. It focuses on how to collect data, highlighting the importance of sampling and experimental design in conducting rigorous science. It presents a variety of key topics specifically related to environmental science such as monitoring, impact assessment, risk assessment, correlated and censored data analysis, to name just a few.
Revised, updated or expanded material on:
- Data Quality Objectives
- Generalized Linear Models
- Spatial Data Analysis
- Censored Data
- Monte Carlo Risk Assessment
There are numerous books on environmental statistics; however, while some focus on multivariate methods and others on the basic components of probability distributions and how they can be used for modeling phenomenon, most do not include the material on sampling and experimental design that this one does. It is the variety of coverage, not sacrificing too much depth for breadth, that sets this book apart.
Zielgruppe
Professional
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
The Role of Statistics in Environmental Science. Environmental Sampling. Models for Data. Drawing Conclusions from Data. Environmental Monitoring. Impact Assessment. Assessing Site Reclamation. Time Series Analysis. Spatial Data Analysis. Censored Data. Monte Carlo Risk Assessment.
