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Advanced Sampling Theory with Applications

How Michael’ selected’ Amy Volume I

  • Book
  • © 2003

Overview

Authors:
  1. Sarjinder Singh

    1. Department of Statistics, St. Cloud State University, St. Cloud, USA

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xxviii
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  2. Basic Concepts and Mathematical Notation

    • Sarjinder Singh
    Pages 1-70

  3. Simple Random Sampling

    • Sarjinder Singh
    Pages 71-136

  4. Use of Auxiliary Information: Simple Random Sampling

    • Sarjinder Singh
    Pages 137-294

  5. Use of Auxiliary Information: Probability Proportional to Size and with Replacement (PPSWR) Sampling

    • Sarjinder Singh
    Pages 295-348

  6. Use of Auxiliary Information: Probability Proportional to Size and Without Replacement (PPSWOR) Sampling

    • Sarjinder Singh
    Pages 349-528

  7. Use of Auxiliary Information: Multi-Phase Sampling

    • Sarjinder Singh
    Pages 529-614

  8. Systematic Sampling

    • Sarjinder Singh
    Pages 615-648

  9. Stratified and Post-Stratified Sampling

    • Sarjinder Singh
    Pages 649-764

  10. Non-Overlapping, Overlapping, Post, and Adaptive Cluster Sampling

    • Sarjinder Singh
    Pages 765-828

  11. Multi-Stage, Successive, and Re-Sampling Strategies

    • Sarjinder Singh
    Pages 829-888

  12. Randomized Response Sampling: Tools For Social Surveys

    • Sarjinder Singh
    Pages 889-974

  13. Non-Response and Its Treatments

    • Sarjinder Singh
    Pages 975-1064

  14. Miscellaneous Topics

    • Sarjinder Singh
    Pages 1065-1103

  15. Back Matter

    Pages 1105-1220
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Keywords

About this book

This book is a multi-purpose document. It can be used as a text by teachers, as a reference manual by researchers, and as a practical guide by statisticians. It covers 1165 references from different research journals through almost 1900 citations across 1194 pages, a large number of complete proofs of theorems, important results such as corollaries, and 324 unsolved exercises from several research papers. It includes 159 solved, data-based, real life numerical examples in disciplines such as Agriculture, Demography, Social Science, Applied Economics, Engineering, Medicine, and Survey Sampling. These solved examples are very useful for an understanding of the applications of advanced sampling theory in our daily life and in diverse fields of science. An additional 173 unsolved practical problems are given at the end of the chapters. University and college professors may find these useful when assigning exercises to students. Each exercise gives exposure to several complete research papers for researchers/students.

Authors and Affiliations

  • Department of Statistics, St. Cloud State University, St. Cloud, USA

    Sarjinder Singh

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