Practical statistics for field biology / Jim Fowler, Louis Cohen, Phil Jarvis.
Material type:
TextPublication details: England : Wiley, Chichester, 2009.Edition: Second editionDescription: 296 pages : illustrations, graphs, genealogical tables ; 25 cmContent type: - text
- unmediated
- volume
- 9780471982968
- 570.727 FOW
| Item type | Current library | Call number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|
| Books | Govt. Graduate College Gulberg, Lahore - Central Library | 570.727 FOW (Browse shelf(Opens below)) | Available | 14031 |
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| 570.28 CLA Statistics and experimental design / | 570.72 RAO Statistical research methods in the life sciences / | 570.72 YOU SAS companion for P.V. Rao's Statistical research methods in the life sciences / | 570.727 FOW Practical statistics for field biology / | 571.1 AGA Animal physiology and biochemistry / | 571.1 VER Animal physiology / | 571.1 VER Animal physiology / |
Includes bibliography and index.
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.
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