LEADER 05672nam 2200757Ia 450 001 9910139399903321 005 20200520144314.0 010 $a9786613371676 010 $a9781283371674 010 $a1283371677 010 $a9781118102213 010 $a1118102215 010 $a9780470650899 010 $a0470650893 010 $a9780470650707 010 $a0470650702 035 $a(CKB)2480000000008343 035 $a(EBL)699162 035 $a(SSID)ssj0000506371 035 $a(PQKBManifestationID)11332880 035 $a(PQKBTitleCode)TC0000506371 035 $a(PQKBWorkID)10515216 035 $a(PQKB)10571246 035 $a(MiAaPQ)EBC699162 035 $a(PPN)170218473 035 $a(FR-PaCSA)88803224 035 $a(OCoLC)676968865 035 $a(FRCYB88803224)88803224 035 $a(Perlego)1013211 035 $a(EXLCZ)992480000000008343 100 $a20100309d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistics for earth and environmental scientists /$fJohn H. Schuenemeyer, Lawrence J. Drew 210 $aHoboken, N.J. $cWiley$dc2011 215 $a1 online resource (422 p.) 300 $aDescription based upon print version of record. 311 08$a9780470584699 311 08$a0470584696 320 $aIncludes bibliographical references (p. 389-397) and index. 327 $aStatistics 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 327 $a1.19 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 327 $a3.6 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 327 $a4.5 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 327 $a7.6 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 327 $a10.3 SPHERICAL DATA 330 $aA 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 517 3 $aEarth and environmental scientists 606 $aGeology$xStatistical methods 606 $aEarth sciences$xStatistical methods 606 $aEnvironmental sciences$xStatistical methods 615 0$aGeology$xStatistical methods. 615 0$aEarth sciences$xStatistical methods. 615 0$aEnvironmental sciences$xStatistical methods. 676 $a550.72/7 700 $aSchuenemeyer$b J. H$0522148 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910139399903321 996 $aStatistics for earth and environmental scientists$94186864 997 $aUNINA