? The book provides case studies illustrating common problems thatexist in natural resource sciences, and presents the statisticalknowledge and tools needed for a modem treatment of these issues.?(APADE, 2009)
"The book's strength lie in the choice of material, theexplication of methods and use, and detail of the code provided ? The bottom line is this book is useful. It is designated notmerely to give you a sense of these often-neglected statisticalmethods but to get you up and running on them. It does aphenomenal job of that task.„ (Ecology, November 2008)
“Stauffer's book seems very suitable for second statistics onmodern regression modeling focusing on Bayesian thinking.„(Journal of the American Statistician, December 2008)
“Stauffer's book seems very suitable for second statistics onmodern regression modeling focusing on Bayesian thinking.„(Journal of the American Statistician, Dec 2008)
“This is an excellent book presenting difficult statisticalideals by using data obtained from real-life situations.„(CHOICE May 2008)
“An ideal text for natural resource students studyingstatistical research methods at the upper-undergraduate or graduatelevel and also service as a valuable problem-solving guide."(Mathematical Reviews 2008)
Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists
von Howard B. StaufferThe use of Bayesian statistical analysis has become increasinglyimportant to natural resource scientists as a practical tool forsolving various research problems. However, many importantcontemporary methods of applied statistics, such as generalizedlinear modeling, mixed-effects modeling, and Bayesian statisticalanalysis and inference, remain relatively unknown among researchersand practitioners in this field. Through its inclusive, hands-ontreatment of real-world examples, Contemporary Bayesian andFrequentist Statistical Research Methods for Natural ResourceScientists successfully introduces the key concepts ofstatistical analysis and inference with an accessible, easy-to-follow approach.
The book provides case studies illustrating common problems thatexist in the natural resource sciences and presents the statisticalknowledge and tools needed for a modern treatment of these issues. Subsequent chapter coverage features:
* An introduction to the fundamental concepts of Bayesianstatistical analysis, including its historical background, conjugate solutions, Bayesian hypothesis testing anddecision-making, and Markov Chain Monte Carlo solutions
* The relevant advantages of using Bayesian statistical analysis, rather than the traditional frequentist approach, to addressresearch problems
* Two alternative strategiesâEUR„the a posteriorimodel selection strategy and the a priori parsimonious modelselection strategy using AIC and DICâEUR“to modelselection and inference
* The ideas of generalized linear modeling (GLM), focusing on themost popular GLM of logistic regression
* An introduction to mixed-effects modeling in S-Plus®and R for analyzing natural resource data sets with varying errorstructures and dependencies
Each statistical concept is accompanied by an illustration ofits frequentist application in S-Plus® or R as well asits Bayesian application in WinBUGS. Brief introductions to thesesoftware packages are also provided to help the reader fullyunderstand the concepts of the statistical methods that arepresented throughout the book. Assuming only a minimal backgroundin introductory statistics, Contemporary Bayesian andFrequentist Statistical Research Methods for Natural ResourceScientists is an ideal text for natural resource studentsstudying statistical research methods at the upper-undergraduate orgraduate level and also serves as a valuable problem-solving guidefor natural resource scientists across a broad range ofdisciplines, including biology, wildlife management, forestrymanagement, fisheries management, and the environmentalsciences.
