Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists (PDF)

The first all-inclusive introduction to modern statistical research
methods in the natural resource sciences

The use of Bayesian statistical analysis has become increasingly
important to natural resource scientists as a practical tool for
solving various research problems. However, many important
contemporary methods of applied statistics, such as generalized
linear modeling, mixed-effects modeling, and Bayesian statistical
analysis and inference, remain relatively unknown among researchers
and practitioners in this field. Through its inclusive, hands-on
treatment of real-world examples, Contemporary Bayesian and
Frequentist Statistical Research Methods for Natural Resource
Scientists successfully introduces the key concepts of
statistical analysis and inference with an accessible,
easy-to-follow approach.

The book provides case studies illustrating common problems that
exist in the natural resource sciences and presents the statistical
knowledge and tools needed for a modern treatment of these issues.
Subsequent chapter coverage features:

* An introduction to the fundamental concepts of Bayesian
statistical analysis, including its historical background,
conjugate solutions, Bayesian hypothesis testing and
decision-making, and Markov Chain Monte Carlo solutions

* The relevant advantages of using Bayesian statistical analysis,
rather than the traditional frequentist approach, to address
research problems

* Two alternative strategiesâEUR"the a posteriori
model selection strategy and the a priori parsimonious model
selection strategy using AIC and DICâEUR"to model
selection and inference

* The ideas of generalized linear modeling (GLM), focusing on the
most popular GLM of logistic regression

* An introduction to mixed-effects modeling in S-Plus®
and R for analyzing natural resource data sets with varying error
structures and dependencies

Each statistical concept is accompanied by an illustration of
its frequentist application in S-Plus® or R as well as
its Bayesian application in WinBUGS. Brief introductions to these
software packages are also provided to help the reader fully
understand the concepts of the statistical methods that are
presented throughout the book. Assuming only a minimal background
in introductory statistics, Contemporary Bayesian and
Frequentist Statistical Research Methods for Natural Resource
Scientists is an ideal text for natural resource students
studying statistical research methods at the upper-undergraduate or
graduate level and also serves as a valuable problem-solving guide
for natural resource scientists across a broad range of
disciplines, including biology, wildlife management, forestry
management, fisheries management, and the environmental
sciences.