Description
Taylor & Francis Ltd Statistics For Environmental Science & Management 2Nd Edition 2008 by Bryan F.J. Manly
Revised, expanded, and updated, this second edition of Statistics for Environmental Science and Management is that rare animal, a resource that works well as a text for graduate courses and a reference for appropriate statistical approaches to specific environmental problems. It is uncommon to find so many important environmental topics covered in one book. Its strength is author Bryan Manly's ability to take a non-mathematical approach while keeping essential mathematical concepts intact. He clearly explains statistics without dwelling on heavy mathematical development. The book begins by describing the important role statistics play in environmental science. It focuses on how to collect data, highlighting the importance of sampling and experimental design in conducting rigorous science. It presents a variety of key topics specifically related to environmental science such as monitoring, impact assessment, risk assessment, correlated and censored data analysis, to name just a few. Revised, updated or expanded material on:Data Quality ObjectivesGeneralized Linear ModelsSpatial Data AnalysisCensored DataMonte Carlo Risk AssessmentThere are numerous books on environmental statistics; however, while some focus on multivariate methods and others on the basic components of probability distributions and how they can be used for modeling phenomenon, most do not include the material on sampling and experimental design that this one does. It is the variety of coverage, not sacrificing too much depth for breadth, that sets this book apart. The Role of Statistics in Environmental ScienceIntroductionSome ExamplesThe Importance of Statistics in the ExamplesChapter SummaryExercisesEnvironmental SamplingIntroductionSimple Random SamplingEstimation of Population MeansEstimation of Population TotalsEstimation of ProportionsSampling and Nonsampling ErrorsStratified Random SamplingPost-StratificationSystematic SamplingOther Design StrategiesRatio EstimationDouble Sampling0Choosing Sample Sizes1Unequal-Probability SamplingThe Data Quality Objectives ProcessChapter SummaryExercisesModels for DataStatistical ModelsDiscrete Statistical DistributionsContinuous Statistical DistributionsThe Linear Regression Model8Factorial Analysis of VarianceGeneralized Linear ModelsChapter SummaryExercisesDrawing Conclusions from DataIntroductionObservational and Experimental StudiesTrue Experiments and Quasi-ExperimentsDesign-Based and Model-Based InferenceTests of Significance and Confidence IntervalsRandomization TestsBootstrappingPseudoreplicationMultiple TestingMeta-AnalysisBayesian InferenceChapter SummaryExercisesEnvironmental MonitoringIntroductionPurposely Chosen Monitoring SitesTwo Special Monitoring Designs6Designs Based on OptimizationMonitoring Designs Typically UsedDetection of Changes by Analysis of VarianceDetection of Changes Using Control ChartsDetection of Changes Using CUSUM ChartsChi-Squared Tests for a Change in a DistributionChapter SummaryExercisesImpact AssessmentIntroductionThe Simple Difference Analysis with BACI DesignsMatched Pairs with a BACI Design.Impact-Control DesignsBefore-After DesignsImpact-Gradient DesignsInferences from Impact Assessment StudiesChapter SummaryExercisesAssessing Site ReclamationIntroductionProblems with Tests of SignificanceThe Concept of BioequivalenceTwo-Sided Tests of BioequivalenceChapter SummaryExercisesTime Series AnalysisIntroductionComponents of Time SeriesSerial CorrelationTests for RandomnessDetection of Change Points and TrendsMore-Complicated Time Series ModelsFrequency Domain AnalysisForecastingChapter SummaryExercisesSpatial-Data AnalysisIntroductionTypes of Spatial DataSpatial Patterns in Quadrat CountsCorrelation between Quadrat CountsRandomness of Point PatternsCorrelation between Point PatternsMantel Tests for AutocorrelationThe VariogramKrigingCorrelation between Variables in SpaceChapter SummaryExercisesCensored DataIntroductionSingle Sample EstimationEstimation of QuantilesComparing the Means of Two or More SamplesRegression with Censored DataChapter SummaryExercisesMonte Carlo Risk AssessmentIntroductionPrinciples for Monte Carlo Risk AssessmentRisk Analysis Using a SpreadsheetChapter SummaryExercisesFinal RemarksAppendicesReferencesIndex