ENGLISH

Introduction to Probability and Statistics for Ecosystem Managers: Simulation and Resampling

By Timothy C. Haas(auth.)

Book information

Year
2013
ISBN
9781118357682, 9781118636206
DOI
10.1002/9781118636206
Language
english
Format
PDF
Filesize
3 MB (2902362 bytes)
Pages
306\306
Orientation
yes
Scanned
yes
Time added
2013-08-01 04:00:00

Description

Explores computer-intensive probability and statistics for ecosystem management decision makingSimulation is an accessible way to explain probability and stochastic model behavior to beginners. This book introduces probability and statistics to future and practicing ecosystem managers by providing a comprehensive treatment of these two areas. The author presents a self-contained introduction for individuals involved in monitoring, assessing, and managing ecosystems and features intuitive, simulation-based explanations of probabilistic and statistical concepts. Mathematical programming details are provided for estimating ecosystem model parameters with Minimum Distance, a robust and computer-intensive method.The majority of examples illustrate how probability and statistics can be applied to ecosystem management challenges. There are over 50 exercises – making this book suitable for a lecture course in a natural resource and/or wildlife management department, or as the main text in a program of self-study.Key features:Reviews different approaches to wildlife and ecosystem management and inference.Uses simulation as an accessible way to explain probability and stochastic model behavior to beginners.Covers material from basic probability through to hierarchical Bayesian models and spatial/ spatio-temporal statistical inference.Provides detailed instructions for using R, along with complete R programs to recreate the output of the many examples presented.Provides an introduction to Geographic Information Systems (GIS) along with examples from Quantum GIS, a free GIS software package.A companion website featuring all R code and data used throughout the book.Solutions to all exercises are presented along with an online intelligent tutoring system that supports readers who are using the book for self-study.Content: Chapter 1 Introduction (pages 1–15): Chapter 2 Probability and Simulation (pages 17–42): Chapter 3 Application of Probability: Models of Political Decision Making in Ecosystem Management (pages 43–59): Chapter 4 Statistical Inference I: Basic Ideas and Parameter Estimation (pages 61–82): Chapter 5 Statistical Inference II: Hypothesis Tests (pages 83–116): Chapter 6 Introduction to spatial statistics (pages 117–158): Chapter 7 Introduction to Spatio?Temporal Statistics (pages 159–197): Chapter 8 Application of Statistical Inference: Estimating the Parameters of an Individual?Based Model (pages 199–221): Chapter 9 Guiding an Influence Diagram's Learning (pages 223–234): Chapter 10 Fitting and Testing a Political–Ecological Simulator (pages 235–255):

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