Statistics for earth and environmental scientists / / John H. Schuenemeyer, Lawrence J. Drew

• Record Nr.: UNINA9910139399903321
• Autore: Schuenemeyer J. H
• Pubbl/distr/stampa: Hoboken, N.J., : Wiley, c2011
• ISBN: 1-283-37167-7; 9786613371676; 1-118-10221-5; 0-470-65089-3; 0-470-65070-2
• Descrizione fisica: 1 online resource (422 p.)
• Disciplina: 550.72/7
• Soggetti: Geology - Statistical methods; Earth sciences - Statistical methods; Environmental sciences - Statistical methods
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. 389-397) and index.
• Nota di contenuto: Statistics for Earth and Environmental Scientists; Contents; Preface; 1 Role of Statistics and Data Analysis; 1.1 INTRODUCTION; 1.2 CASE STUDIES; 1.3 DATA; 1.4 SAMPLES VERSUS THE POPULATION: SOME NOTATION; 1.5 VECTOR AND MATRIX NOTATION; 1.6 FREQUENCY DISTRIBUTIONS AND HISTOGRAMS; 1.7 DISTRIBUTION AS A MODEL; 1.8 SAMPLE MOMENTS; 1.9 NORMAL (GAUSSIAN) DISTRIBUTION; 1.10 EXPLORATORY DATA ANALYSIS; 1.11 ESTIMATION; 1.12 BIAS; 1.13 CAUSES OF VARIANCE; 1.14 ABOUT DATA; 1.15 REASONS TO CONDUCT STATISTICALLY BASED STUDIES; 1.16 DATA MINING; 1.17 MODELING; 1.18 TRANSFORMATIONS; 1.19 STATISTICAL CONCEPTS1.20 STATISTICS PARADIGMS; 1.21 SUMMARY; EXERCISES; 2 Modeling Concepts; 2.1 INTRODUCTION; 2.2 WHY CONSTRUCT A MODEL?; 2.3 WHAT DOES A STATISTICAL MODEL DO?; 2.4 STEPS IN MODELING; 2.5 IS A MODEL A UNIQUE SOLUTION TO A PROBLEM?; 2.6 MODEL ASSUMPTIONS; 2.7 DESIGNED EXPERIMENTS; 2.8 REPLICATION; 2.9 SUMMARY; EXERCISES; 3 Estimation and Hypothesis Testing on Means and Other Statistics; 3.1 INTRODUCTION; ; 3.2 INDEPENDENCE OF OBSERVATIONS; 3.3 CENTRAL LIMIT THEOREM; 3.4 SAMPLING DISTRIBUTIONS; 3.5 CONFIDENCE INTERVAL ESTIMATE ON A MEAN; 3.6 CONFIDENCE INTERVAL ON THE DIFFERENCE BETWEEN MEANS3.7 HYPOTHESIS TESTING ON MEANS; 3.8 BAYESIAN HYPOTHESIS TESTING; 3.9 NONPARAMETRIC HYPOTHESIS TESTING; 3.10 BOOTSTRAP HYPOTHESIS TESTING ON MEANS; 3.11 TESTING MULTIPLE MEANS VIA ANALYSIS OF VARIANCE; 3.12 MULTIPLE COMPARISONS OF MEANS; 3.13 NONPARAMETRIC ANOVA; 3.14 PAIRED DATA; 3.15 KOLMOGOROV-SMIRNOV GOODNESS-OF-FIT TEST; 3.16 COMMENTS ON HYPOTHESIS TESTING; 3.17 SUMMARY; EXERCISES; 4 Regression; 4.1 INTRODUCTION; 4.2 PITTSBURGH COAL QUALITY CASE STUDY; 4.3 CORRELATION AND COVARIANCE; 4.4 SIMPLE LINEAR REGRESSION; 4.5 MULTIPLE REGRESSION4.6 OTHER REGRESSION PROCEDURES; 4.7 NONLINEAR MODELS; 4.8 SUMMARY; EXERCISES; 5 Time Series; 5.1 INTRODUCTION; 5.2 TIME DOMAIN; 5.3 FREQUENCY DOMAIN; 5.4 WAVELETS; 5.5 SUMMARY; EXERCISES; 6 Spatial Statistics; 6.1 INTRODUCTION; 6.2 DATA; 6.3 THREE-DIMENSIONAL DATA VISUALIZATION; 6.4 SPATIAL ASSOCIATION; 6.5 EFFECT OF TREND; 6.6 SEMIVARIOGRAM MODELS; 6.7 KRIGING; 6.8 SPACE-TIME MODELS; 6.9 SUMMARY; EXERCISES; 7 Multivariate Analysis; 7.1 INTRODUCTION; 7.2 MULTIVARIATE GRAPHICS; 7.3 PRINCIPAL COMPONENTS ANALYSIS; 7.4 FACTOR ANALYSIS; 7.5 CLUSTER ANALYSIS; 7.6 MULTIDIMENSIONAL SCALING7.7 DISCRIMINANT ANALYSIS; 7.8 TREE-BASED MODELING; 7.9 SUMMARY; EXERCISES; 8 Discrete Data Analysis and Point Processes; 8.1 INTRODUCTION; 8.2 DISCRETE PROCESS AND DISTRIBUTIONS; 8.3 POINT PROCESSES; 8.4 LATTICE DATA AND MODELS; 8.5 PROPORTIONS; 8.6 CONTINGENCY TABLES; 8.7 GENERALIZED LINEAR MODELS; 8.8 SUMMARY; EXERCISES; 9 Design of Experiments; 9.1 INTRODUCTION; 9.2 SAMPLING DESIGNS; 9.3 DESIGN OF EXPERIMENTS; 9.4 COMMENTS ON FIELD STUDIES AND DESIGN; 9.5 MISSING DATA; 9.6 SUMMARY; EXERCISES; 10 Directional Data; 10.1 INTRODUCTION; 10.2 CIRCULAR DATA; 10.3 SPHERICAL DATA
• Sommario/riassunto: A comprehensive treatment of statistical applications for solving real-world environmental problems A host of complex problems face today's earth science community, such as evaluating the supply of remaining non-renewable energy resources, assessing the impact of people on the environment, understanding climate change, and managing the use of water. Proper collection and analysis of data using statistical techniques contributes significantly toward the solution of these problems. Statistics for Earth and Environmental Scientists presents important statistical concepts through data analyt