This edited volume explains data analysis methods, examples, exercises and case-studies.Originally published in 1987, the purpose of this reissue is to show ecologists and environmental scientists the most useful numerical and statistical methods and how to interpret results and avoid pitfalls. Written for ecologists, it explains such techniques as logistic regression, canonical correspondence analysis, and kriging. Originally published in 1987, the purpose of this reissue is to show ecologists and environmental scientists the most useful numerical and statistical methods and how to interpret results and avoid pitfalls. Written for ecologists, it explains such techniques as logistic regression, canonical correspondence analysis, and kriging. Ecologists need to analyze their field data to interpret relationships within plant and animal communities and with their environments. The purpose of this book is to show ecologists and environmental scientists what numerical and statistical methods are most useful, how to use them and interpret the results from them, and what pitfalls to avoid. Subjects treated include data requirements, regression analysis, calibration (or inverse regression), ordination techniques, cluster analysis, and spatial analysis of ecological data. The authors take pains to use only elementary mathematics and explain the ecological models behind the techniques. Exercises and solution are provided for practice. This is the only book written specifically for ecologists that explains such techniques as logistic regression, canonical correspondence analysis, and kriging (statistical manipulation of data). This is a reissue of a book first published in 1987 by Pudoc (The Netherlands).List of contributors; Preface to first edition; Acknowledgement; List of symbols; Dune meadow data; 1. Introduction R. H. G. Jongman; 2. Data collection J. C. Jager and C. W. N. Looman; 3. Regression C. J. F. ter Braak and C. W. N. Looman; 4. Calibration C. J. F. ter Bl³»