Ecological research is becoming increasingly quantitative, yet
students often opt out of courses in mathematics and statistics,
unwittingly limiting their ability to carry out research in the
future. This textbook provides a practical introduction to
quantitative ecology for students and practitioners who have
realised that they need this opportunity.
The text is addressed to readers who haven't used mathematics
since school, who were perhaps more confused than enlightened by
their undergraduate lectures in statistics and who have never used
a computer for much more than word processing and data entry. From
this starting point, it slowly but surely instils an understanding
of mathematics, statistics and programming, sufficient for
initiating research in ecology. The book's practical value is
enhanced by extensive use of biological examples and the computer
language R for graphics, programming and data analysis.
Key Features: Provides a complete introduction to mathematics
statistics and computing for ecologists.Presents a wealth of
ecological examples demonstrating the applied relevance of abstract
mathematical concepts, showing how a little technique can go a long
way in answering interesting ecological questions.Covers elementary
topics, including the rules of algebra, logarithms, geometry,
calculus, descriptive statistics, probability, hypothesis testing
and linear regression.Explores more advanced topics including
fractals, non-linear dynamical systems, likelihood and Bayesian
estimation, generalised linear, mixed and additive models, and
multivariate statistics.R boxes provide step-by-step recipes for
implementing the graphical and numerical techniques outlined in
each section.
"How to be a Quantitative Ecologist" provides a comprehensive
introduction to mathematics, statistics and computing and is the
ideal textbook for late undergraduate and postgraduate courses in
environmental biology.
"With a book like this, there is no excuse for people to be
afraid of maths, and to be ignorant of what it can do."
--Professor Tim Benton, Faculty of Biological Sciences, University
of Leeds, UK
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