How to be a Quantitative Ecologist (PDF)

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