How to Be a Quantitative Ecologist - The ''A to R'' of Green Mathematics and Statistics

Informationen zum Autor Jason Matthiopoulos , Lecturer in biology (University of St Andrews). He is a senior researcher in the Sea Mammal Research Unit and member of the Centre for Ecological and Environmental Modelling. Klappentext 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 Zusammenfassung How to Be a Quantitative Ecologist is comprised of two equal parts on mathematics and statistics with emphasis on quantitative skills. A major component of this guide is computer implementation techniques, accompanied by computer practicals using the language R. Inhaltsverzeichnis How I chose to write this book, and why you might choose to read it. Preface. 0. How to start a meaningful relationship with your computer. Introduction to R. 0.1 What is R? 0.2 Why use R for this book? 0.3 Computing with a scientific package like R. 0.4 Installing and interacting with R. 0.5 Style conventions. 0.6 Valuable R accessories. 0.7 Getting help. 0.8 Basic R usage. 0.9 Importing data from a spreadsheet. 0.10 Storing data in data frames. 0.11 Exporting data from R. 0.12 Quitting R. 1. How to make mathematical statements. Numbers, equations and functions. 1.1 Qualitative and quantitative scales. 1.2 Numbers. 1.3 Symbols. 1.4 Logical operations. 1.5 Algebraic operations. 1.6 Manipulating numbers. 1.7 Manipulating units. 1.8 Manipulating expressions. 1.9 Polynomials. 1.10 Equations. 1.11 First order polynomial equations. 1.12 Proportionality and scaling: a special kind of first order polynomial equation. 1.13 Second and higher order polynomial equations. 1.14 Systems of polynomial equations. 1.15 ...

Sommario

How I chose to write this book, and why you might choose to read it.
 
Preface.
 
0. How to start a meaningful relationship with your computer.
 
Introduction to R.
 
0.1 What is R?
 
0.2 Why use R for this book?
 
0.3 Computing with a scientific package like R.
 
0.4 Installing and interacting with R.
 
0.5 Style conventions.
 
0.6 Valuable R accessories.
 
0.7 Getting help.
 
0.8 Basic R usage.
 
0.9 Importing data from a spreadsheet.
 
0.10 Storing data in data frames.
 
0.11 Exporting data from R.
 
0.12 Quitting R.
 
1. How to make mathematical statements.
 
Numbers, equations and functions.
 
1.1 Qualitative and quantitative scales.
 
1.2 Numbers.
 
1.3 Symbols.
 
1.4 Logical operations.
 
1.5 Algebraic operations.
 
1.6 Manipulating numbers.
 
1.7 Manipulating units.
 
1.8 Manipulating expressions.
 
1.9 Polynomials.
 
1.10 Equations.
 
1.11 First order polynomial equations.
 
1.12 Proportionality and scaling: a special kind of first order polynomial equation.
 
1.13 Second and higher order polynomial equations.
 
1.14 Systems of polynomial equations.
 
1.15 Inequalities.
 
1.16 Coordinate systems.
 
1.17 Complex numbers.
 
1.18 Relations and functions.
 
1.19 The graph of a function.
 
1.20 First order polynomial functions.
 
1.21 Higher order polynomial functions.
 
1.22 The relationship between equations and functions.
 
1.23 Other useful functions.
 
1.24 Inverse functions.
 
1.25 Functions of more than one variable.
 
2. How to describe regular shapes and patterns.
 
Geometry and trigonometry.
 
2.1 Primitive elements.
 
2.2 Axioms of Euclidean geometry.
 
2.3 Propositions.
 
2.4 Distance between two points.
 
2.5 Areas and volumes.
 
2.6 Measuring angles.
 
2.7 The trigonometric circle.
 
2.8 Trigonometric functions.
 
2.9 Polar coordinates.
 
2.10 Graphs of trigonometric functions.
 
2.11 Trigonometric identities.
 
2.12 Inverses of trigonometric functions.
 
2.13 Trigonometric equations.
 
2.14 Modifying the basic trigonometric graphs.
 
2.15 Superimposing trigonometric functions.
 
2.16 Spectral analysis.
 
2.17 Fractal geometry.
 
3. How to change things, one step at a time.
 
Sequences, difference equations and logarithms.
 
3.1 Sequences.
 
3.2 Difference equations.
 
3.3 Higher order difference equations.
 
3.4 Initial conditions and parameters.
 
3.5 Solutions of a difference equation.
 
3.6 Equilibrium solutions.
 
3.7 Stable and unstable equilibria.
 
3.8 Investigating stability.
 
3.9 Chaos.
 
3.10 Exponential function.
 
3.11 Logarithmic function.
 
3.12 Logarithmic equations.
 
4. How to change things, continuously.
 
Derivatives and their applications.
 
4.1 Average rate of change.
 
4.2 Instantaneous rate of change.
 
4.3 Limits.
 
4.4 The derivative of a function.
 
4.5 Differentiating polynomials.
 
4.6 Differentiating other functions.
 
4.7 The chain rule.
 
4.8 Higher order derivatives.
 
4.9 Derivatives of functions of many variables.
 
4.10 Optimisation.
 
4.11 Local stability for difference equations.
 
4.12 Series expansions.
&n

Relazione

"For those looking through R books for something a bit more technical, this book will be an essential accomplice to mastering R." (British Ecological Society, 1 April 2013)
 
"The book is written in a style that is easy to read and for which one quickly forgets that the examples are essentially mathematical in nature. If you are an ecologist who has shied away from quantitative ecology in the past then this may be the text to convince you that there is much to be learnt from quantitative ecology. I thoroughly recommend this book and trust that you enjoy reading it as much as I did." (International Statistical Review, 2012) "After a course of one or two semesters using this textbook, he says, students should have the absolute minimum of knowledge about quantitative research that ecologists need, but can provide a foundation for students who want to move further in that direction." (Book News, 1 August 2011)

Dettagli sul prodotto

• Autori: Matthiopoulos, J Matthiopoulos, Jason Matthiopoulos, Jason (Scottish Oceans Institute & Matthiopoulos, Matthiopoulos Jason
• Editore: Wiley, John and Sons Ltd
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 18.04.2011
• EAN: 9780470699799
• ISBN: 978-0-470-69979-9
• Pagine: 496
• Categorie: Scienze naturali, medicina, informatica, tecnica > Biologia > Ecologia; Statistik, Mathematik, Geowissenschaften, Statistics, Life Sciences, Biowissenschaften, Earth Sciences, Methods & Statistics in Ecology, Ökologie / Methoden, Statistik, Environmental Geoscience, Umweltgeowissenschaften, Umweltstatistik u. Environmetrics, Environmental Statistics & Environmetrics