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Statistics for Ecologists Using R and Excel Paperback – 1 Oct 2011


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Product details

  • Paperback: 324 pages
  • Language: English
  • ISBN-10: 1907807128
  • ISBN-13: 978-1907807121
  • Product Dimensions: 17 x 1.8 x 24.4 cm
  • Boxed-product Weight: 540 g
  • Average Customer Review: Be the first to review this item

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Review

The text that I have found most helpful in getting back to using R has been Mark Gardener's Statistics for Ecologists Using R and Excel. This excellent little book leads the reader nicely through the basics. Starting with how to down load R and getting data into the programme through exploratory statistics and into basic analysis with a section on reporting results which includes visualising data. It also makes it easy for the reader to synthesise R and Excel and there is extra help and sample data available on the free companion webpage if needed. I recommended this text to the university library as well as to colleagues at my student workshops on R. Although I initially bought this book when I wanted to discover R I actually also learned new techniques for data manipulation and management in Excel. -- Mark Edwards EcoBlogging

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.

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