# Practical Statistics for Field Biology 2e

## Jim FOWLER

Yayınevi: John Wiley High Education

Yayın tarihi: 05/1998

ISBN: 9780471982968

Yazar : Lou Cohen Phil Jarvis

İngilizce | 272 Sayfa |

Tür: Biyoloji-Genetik

• Temin Süresi 28 - 42 iş günü

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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 peculiarities of field-based data and its interpretation, Practical Statistics for Field Biology introduces readers to the principles and methods of statistical analysis allowing them to understand research reports in journals, decide on the most appropriate statistical tests for their own problems and finally to analyse and present their findings. 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 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. Practical Statistics for Field biology will be of interest to undergraduates studying ecology, biology, and earth and environmental sciences. In addition, it will be useful for postgraduates who are not familiar with the application of multivariate techniques and practising field biologists working in these areas.

Measurement and Sampling Concepts.
Processing Data.
Presenting Data.
Measuring the Average.
Measuring Variability.
Probability.
Probability Distributions as Models of Dispersion.
The Normal Distribution.
Data Transformation.
How Good are Our Estimates?
The Basis of Statistical Testing.
Analysing Frequencies.
Measuring Correlations.
Regression Analysis.
Comparing Averages.
Analysis of Variance - ANOVA.
Multivariate Analysis.
Appendices.
Index.

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