Provides an excellent introductory text for students on the principles and methods of statistical analysis in the life sciences, helping them choose and analyse statistical tests for their own problems and present their findings. An understanding of statistical principles and methods is essential for any scientist but is particularly important for those in the life sciences. The field biologist faces very particular problems and challenges with statistics as "real-life" situations such as collecting insects with a sweep net or counting seagulls on a cliff face can hardly be expected to be as reliable or controllable as a laboratory-based experiment. Acknowledging the peculiarites of field-based data and its interpretation, this book provides a superb introduction to statistical analysis helping students relate to their particular and often diverse data with confidence and ease. To enhance the usefulness of this book, the new edition incorporates the more advanced method of multivariate analysis, introducing the nature of multivariate problems and describing the the techniques of principal components analysis, cluster analysis and discriminant analysis which are all applied to biological examples. An appendix detailing the statistical computing packages available has also been included. It will be extremely useful to undergraduates studying ecology, biology, and earth and environmental sciences and of interest to postgraduates who are not familiar with the application of multiavirate techniques and practising field biologists working in these areas.
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Read for BI393: Biostatistics. A solid introduction to biological research. Long-hand examples could be argued as unnecessary in the age of statistical software programs, but theoretical background is important.
This book was an absolute god-send during my studies. If you've no head for maths and have to use them this is definitely the book for you. It's clearly written and details what each method is best used for and gives easy to follow examples. This book was always beside my computer throughout my studies and I keep it handy even now.
Even after so many years I still find this book immensely useful. But now with the advent of so many easy to use stats software this is now better as a reference guide than a means of working these out by hand (thankfully as those tables are scary!).