Overview
- Discusses all major topics on sampling theory and estimation with their applications
- Highlights the importance of the cost-efficient sampling and introduces a new method to control the size of a sample
- Focuses on applications of sampling in ecology, environmental science, health science, forestry, bio-sciences, and humanities
- Illustrates the applications of sampling methods by using R
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About this book
This book discusses all major topics on survey sampling and estimation. It covers traditional as well as advanced sampling methods related to the spatial populations. The book presents real-world applications of major sampling methods and illustrates them with the R software. As a large sample size is not cost-efficient, this book introduces a new method by using the domain knowledge of the negative correlation between the variable of interest and the auxiliary variable in order to control the size of a sample. In addition, the book focuses on adaptive cluster sampling, rank-set sampling and their applications in real life. Advance methods discussed in the book have tremendous applications in ecology, environmental science, health science, forestry, bio-sciences, and humanities. This book is targeted as a text for undergraduate and graduate students of statistics, as well as researchers in various disciplines.
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Keywords
Table of contents (22 chapters)
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Front Matter
Authors and Affiliations
About the authors
RAOSAHEB LATPATE is Assistant Professor at the Department of Statistics and Center for Advanced Studies, Savitribai Phule Pune University, Pune, India. He completed his Ph.D. from Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India. He has organized three workshops on statistical methods and applications and is a member of a number of professional societies and institutions, including the International Statistical Institute, International Indian Statistical Association, Society for Statistics and Computer Applications, and the Indian Society for Probability and Statistics. His research interests include genetic algorithm, fuzzy set theory, supply chain management, logistics and transportation problem, simulation and modelling, and sample survey.
JAYANT KSHIRSAGAR is Principle at Ekta Shikshan Prasarak Mandal's Arts, Commerce and Science College, Ahmednagar, India. Earlier, he was Associate Professor of Statistics in New Arts, Commerce and Science College,Ahmednagar, India. He has been teaching statistics to undergraduate students for over 38 years and 8 years to postgraduate students. He has published over 15 research papers in reputed national and international journals and presented research papers in national and international conferences. His research interests include sampling designs, bio-statistics and mathematical statistics.
VINOD KUMAR GUPTA is former ICAR National Professor of Indian Agricultural Statistics Research Institute, New Delhi, India. He received his Ph.D. in Agricultural Statistics from Indian Agricultural Research Institute (IARI), New Delhi, in 1983. His areas of research are design of experiments, theory of survey sampling and applied statistics. He has authored over 140 research papers, 4 books, 30 research project reports, several monographs, teaching manuals, electronic manuals, and popular articles, and more than 10 special volumes of journals as guest editor. Under his supervision, 11 students have completed their Ph.D. degrees.
He is associated with the developments of two very important and popular web resources, namely, Design Resources Server and Sample Surveys Resources Server. He is President of the Society of Statistics, Computer and Applications, New Delhi, India, and President of the Governing Body of Institute of Applied Statistics and Development Studies, Lucknow, India. A Fellow of the National Academy of Agricultural Sciences and that of the Indian Society of Agricultural Statistics, India, Dr. Gupta is the elected member of the International Statistical Institute, the Netherlands. He has been awarded the Sankhyiki Bhushan Award from the Institute of Applied Statistics and Development Studies, India; the P.V. Sukhatme Gold Medal Award and the D.N. Lal Memorial Lecture Award from the Indian Society of Agricultural Statistics, India; and the best teacher award from the PG School of Indian Agricultural Statistics Research Institute, India.
GIRISH CHANDRA is Scientist at the Division of Forestry Statistics, Indian Council of Forestry Research and Education (ICFRE), Dehradun, India. Earlier, he worked with the Tropical Forest Research Institute, Jabalpur, India and Central Agricultural University, Sikkim, India. His research interests include sample surveys, probability theory, applied statistics and applications in forestry and environmental sciences. He has authored 3 books and published over 30 research papers in reputed journals. He is a recipient of the 2017 Cochran–Hansen Prize by the International Association of Survey Statisticians, the Netherlands. He was honored with the 2018 ICFRE Outstanding Research Award as well as the Young Scientist Award in Mathematical Sciences from the Government of Uttarakhand, India. Having organized two national conferences on forestry and environmental statistics, Dr. Chandra is a member of number of professional societies and institutions, namely, the International Statistical Institute, International Indian Statistical Association, Computational and Methodological Statistics, and the Indian Society for Probability and Statistics.
Bibliographic Information
Book Title: Advanced Sampling Methods
Authors: Raosaheb Latpate, Jayant Kshirsagar, Vinod Kumar Gupta, Girish Chandra
DOI: https://doi.org/10.1007/978-981-16-0622-9
Publisher: Springer Singapore
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
Hardcover ISBN: 978-981-16-0621-2Published: 08 May 2021
Softcover ISBN: 978-981-16-0624-3Published: 09 May 2022
eBook ISBN: 978-981-16-0622-9Published: 07 May 2021
Edition Number: 1
Number of Pages: XVII, 301
Number of Illustrations: 10 b/w illustrations, 13 illustrations in colour
Topics: Statistical Theory and Methods, Bayesian Inference, Statistics and Computing/Statistics Programs