Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.
Practical Statistics for Field Biology, 2nd EditionProvides 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.
Jim Fowler, Principal Lecturer, Department of Biological Sciences, De Montfort University, Leicester, UK.Lou Cohen, Emeritus Professor of Education, Loughborough University of Technology, Loughborough, UK.Phil Jarvis, Senior Statistician, Safety of Medicines, Zeneca Pharmaceuticals, Macclesfield, UK.
Preface xi1 Introduction 12 Measurement and Sampling Concepts 33 Processing Data 84 Presenting Data 185 Measuring the Average 266 Measuring Variability 357 Probability 428 Probability Distributions as Models of Dispersion 629 The Normal Distribution 7410 Data Transformation 8311 How Good are Our Estimates? 9012 The Basis of Statistical Testing 10413 Analysing Frequencies 11114 Measuring Correlations 13015 Regression Analysis 14216 Comparing Averages 16517 Analysis of Variance - ANOVA 17918 Multivariate Analysis 210AppendicesBibliography and Further Reading 256Index 257