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The goal of this book is to present skills and knowledge of important statistical concepts through data analytic tools and then apply them to real world problems in the environmental sciences. Each chapter concludes with exercises designed to elicit understanding of the processes of data analysis, model building, and statistical inference.

Taal / Language : English

Inhoudsopgave:
Chapter 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 The 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.

1.15 Reasons to conduct statistically based studies.

1.16 Data mining.

1.17 Modeling.

1.18 Transformations.

1.19 Statistical concepts.

1.21 Summary.

1.22 Exercises.

Chapter 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.

2.10 Exercises.

Chapter 3. Estimation and hypothesis testing on means and other statistics.

3.1 Introduction.

3.2 Independence of observations.

3.3 The Central Limit Theorem.

3.4 Sampling distributions.

3.4.1 t distribution.

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.

3.18 Exercises.

Chapter 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 Summary.

4.9 Exercises.

Chapter 5. Time series.

5.1 Introduction.

5.2 Time Domain.

5.3 Frequency Domain.

5.4 Wavelets.

5.5 Summary.

5.6 Exercises.

Chapter 6. Spatial statistics.

6.1 Introduction.

6.2 Data.

6.3 Three dimensional data visualization.

6.4 Spatial association.

6.5 The effect of trend.

6.6 Semivariogram models.

6.7 Kriging.

6.8 Space time models.

6.9 Summary.

6.10 Exercises.

Chapter 7. Multivariate analysis.

7.1 Introduction.

7.2 Multivariate graphics.

7.3 Principal component 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.

7.10 Exercises.

Chapter 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.

8.9 Exercises.

Chapter 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.

9.7 Exercises.

Chapter 10 Directional data.

10.1 Introduction.

10.2 Circular data.

10.3 Spherical data.

10.4 Summary.

10.5 Exercises.
Extra informatie:
Hardback
384 pagina's
Januari 2011
784 gram
243 x 160 x 28 mm
Wiley-Blackwell

 Winkelwagen
 Levertijd: 5 tot 11 werkdagen

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