- Paperback: 568 pages
- Publisher: Pelagic Publishing Ltd (6 Jan. 2014)
- Language: English
- ISBN-10: 1907807616
- ISBN-13: 978-1907807619
- Product Dimensions: 17 x 2.9 x 24.4 cm
- Average Customer Review: 4.5 out of 5 stars See all reviews (2 customer reviews)
- Amazon Bestsellers Rank: 550,691 in Books (See Top 100 in Books)
- See Complete Table of Contents
Community Ecology: Analytical Methods Using R and Excel (Data in the Wild) Paperback – 6 Jan 2014
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Following an intuitive thread from data entry through to analysis and interpretation, this is intended as a comprehensive course in the main methods of community analysis, both traditional and current. The intimidating length can largely be attributed to the numerous worked examples with full output. Some techniques are demonstrated in both Excel and R, which seems superfluous, since the latter is almost invariably superior. I would have liked more on GREP, an invaluable tool for checking and formatting data, and a notable weakness of Excel. Overall this is a useful resource for postgraduate students, but it could have been more concise and selective.--Markus Eichhorn "Frontiers of Biogeography "
About the Author
Mark Gardener (www.gardenersown.co.uk) is an ecologist, lecturer, and writer working in the UK. His primary area of research was in pollination ecology and he has worked in the UK and around the word (principally Australia and the United States). Since his doctorate he has worked in many areas of ecology, often as a teacher and supervisor. He believes that ecological data, especially community data, is the most complicated and ill-behaved and is consequently the most fun to work with. He was introduced to R by a like-minded pedant whilst working in Australia during his doctorate. Learning R was not only fun but opened up a new avenue, making the study of community ecology a whole lot easier. He is currently self-employed and runs courses in ecology, data analysis, and R for a variety of organizations. Mark lives in rural Devon with his wife Christine, a biochemist who consequently has little need of statistics.