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Statistics for earth and environmental scientists
- Author / Creator
- Available as
- Physical
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- Creator
- John H. Schuenemeyer, Lawrence J. Drew
- Format
- Books
- Language
- English
- Contributors
- Publication
-
- Hoboken, N.J. : Wiley, [2011]
- ©2011
- Physical Details
-
- x, 407 pages : illustrations (some color) ; 25 cm
- ISBNs
- 0470650702, 1283371677, 9780470584699, 9786613371676, 0470584696, 0470650893, 1118102215
- OCLC
- ocn551718601, ocn676968865
- Includes bibliographical references (pages 389-397) and index.
- Machine generated contents note: 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 Concepts -- 1.20. Statistics Paradigms -- 1.21. Summary -- Exercises -- 2. Modeling Concepts -- 2.1. 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 Means -- 3.7. 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 Regression -- 4.6. Other Regression Procedures -- 4.7. Nonlinear Models -- 4.8. 5. Time Series -- 5.1. 5.2. Time Domain -- 5.3. Frequency Domain -- 5.4. Wavelets -- 5.5. 6. Spatial Statistics -- 6.1. 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. 7. Multivariate Analysis -- 7.1. 7.2. Multivariate Graphics -- 7.3. Principal Components Analysis -- 7.4. Factor Analysis
- 7.5. Cluster Analysis -- 7.6. Multidimensional Scaling -- 7.7. 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. 9. Design of Experiments -- 9.1. 9.2. Sampling Designs -- 9.3. 9.4. Comments on Field Studies and Design -- 9.5. Missing Data -- 9.6. 10. Directional Data -- 10.1. 10.2. Circular Data -- 10.3. Spherical Data -- 10.4. Exercises