Description
Practical Statistics for Field Biology, 2nd Edition
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.
Table of Contents
Preface xi
1 Introduction 1
2 Measurement and Sampling Concepts 3
3 Processing Data 8
4 Presenting Data 18
5 Measuring the Average 26
6 Measuring Variability 35
7 Probability 42
8 Probability Distributions as Models of Dispersion 62
9 The Normal Distribution 74
10 Data Transformation 83
11 How Good are Our Estimates? 90
12 The Basis of Statistical Testing 104
13 Analysing Frequencies 111
14 Measuring Correlations 130
15 Regression Analysis 142
16 Comparing Averages 165
17 Analysis of Variance - ANOVA 179
18 Multivariate Analysis 210
Appendices
Bibliography and Further Reading 256
Index 257
