
- 930 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Survey Sampling Theory and Applications
About this book
Survey Sampling Theory and Applications offers a comprehensive overview of survey sampling, including the basics of sampling theory and practice, as well as research-based topics and examples of emerging trends. The text is useful for basic and advanced survey sampling courses. Many other books available for graduate students do not contain material on recent developments in the area of survey sampling.
The book covers a wide spectrum of topics on the subject, including repetitive sampling over two occasions with varying probabilities, ranked set sampling, Fays method for balanced repeated replications, mirror-match bootstrap, and controlled sampling procedures. Many topics discussed here are not available in other text books. In each section, theories are illustrated with numerical examples. At the end of each chapter theoretical as well as numerical exercises are given which can help graduate students.
- Covers a wide spectrum of topics on survey sampling and statistics
- Serves as an ideal text for graduate students and researchers in survey sampling theory and applications
- Contains material on recent developments in survey sampling not covered in other books
- Illustrates theories using numerical examples and exercises
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Survey Sampling Theory and Applications by Raghunath Arnab in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- Preface
- Acknowledgments
- Chapter 1. Preliminaries and Basics of Probability Sampling
- Chapter 2. Unified Sampling Theory: Design-Based Inference
- Chapter 3. Simple Random Sampling
- Chapter 4. Systematic Sampling
- Chapter 5. Unequal Probability Sampling
- Chapter 6. Inference Under Superpopulation Model
- Chapter 7. Stratified Sampling
- Chapter 8. Ratio Method of Estimation
- Chapter 9. Regression, Product, and Calibrated Methods of Estimation
- Chapter 10. Two-Phase Sampling
- Chapter 11. Repetitive Sampling
- Chapter 12. Cluster Sampling
- Chapter 13. Multistage Sampling
- Chapter 14. Variance/Mean Square Estimation
- Chapter 15. Nonsampling Errors
- Chapter 16. Randomized Response Techniques
- Chapter 17. Domain and Small Area Estimation
- Chapter 18. Variance Estimation: Complex Survey Designs
- Chapter 19. Complex Surveys: Categorical Data Analysis
- Chapter 20. Complex Survey Design: Regression Analysis
- Chapter 21. Ranked Set Sampling
- Chapter 22. Estimating Functions
- Chapter 23. Estimation of Distribution Functions and Quantiles
- Chapter 24. Controlled Sampling
- Chapter 25. Empirical Likelihood Method in Survey Sampling
- Chapter 26. Sampling Rare and Mobile Populations
- Author Index
- Subject Index