18 Best Books on Sampling Theory

“Theory and Methods of Survey Sampling” Book Review: This book is an ideal resource for students of course statistics, survey statisticians, and practitioners involved in consultancy services, marketing, opinion polls, etc. It emphasizes the assumptions underlying nonparametric techniques and provides usage of R software to compute and simulate these methods. In addition, the book offers a review of classical techniques of survey sampling, including the prediction-theoretic approach, and covers topics such as variance estimation and analysis of complex surveys, unequal probability sampling, inference from finite populations using classical inference tools, and nonsampling errors, including randomised response techniques. The book also provides examples from a variety of fields, including agricultural science, astronomy, biology, criminology, and education. It introduces density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics. Finally, the book includes a list of problems and solutions to reinforce the concepts presented, making it an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.

“Some Theories of Sampling (Dover Books on Mathematics)” Book Review: The book is a comprehensive resource that offers analysis of sampling techniques, including their problems, theory, and design. It serves as a textbook for those involved in statistics, including social scientists, industrial managers, and others. The book covers the basics of algebra and provides examples of dozens of actual large-scale surveys in government and industry.

“Sampling Theory, a Renaissance (Applied and Numerical Harmonic Analysis)” Book Review: The book explores the tools utilized for uncovering concealed data on classical sampling theorems, showcasing the ongoing renaissance within the field of sampling theory. In addition to this, the book delves into various other topics, including compressed sensing, finite frames, parametric partial differential equations, quantization, finite rate of innovation, and system theory. It also touches on sampling in geometry and algebraic topology.

“Survey Sampling Theory and Applications” Book Review: The book provides an introduction to the fundamentals of sampling theory and practical applications, as well as an overview of survey sampling. The topics covered in the book range from basic to advanced survey sampling courses and include recent developments in the field. These include repetitive sampling over two occasions with varying probabilities, ranked set sampling, Fays method for balanced repeated replications, among others. Each chapter concludes with both theoretical and numerical exercises. Additionally, the book includes research-based topics and examples of emerging trends.

“New Perspectives on Approximation and Sampling Theory (Applied and Numerical Harmonic Analysis)” Book Review: This textbook covers important topics such as approximation, sampling theory, and harmonic analysis. It delves into approximation methods using wavelets, multi-scale analysis, frames, and special functions. Starting with the fundamentals of mathematical analysis and the process of signal and image processing, the book is an ideal resource for graduate students in mathematics, applied mathematics, and engineering.

“Modern Sampling Theory: Mathematics and Applications (Applied and Numerical Harmonic Analysis)” Book Review: This comprehensive book covers all aspects of sampling theory, including its history and development. It provides an overview of the theory, methods, and applications of various topics, ranging from multi-dimensional signal analysis to wavelet transforms. The book also includes a chapter on WSK sampling theory and highlights how sampling theory is connected to more recent topics in mathematical analysis, such as wavelets, Gabor systems, density theorems, and frames.

“Survey Sampling: Theory and Methods, Second Edition (Statistics: A Series of Textbooks and Monographs)” Book Review: The book presents the latest research and cutting-edge methods in survey sampling. It features an expanded coverage of approaches that integrate design and model-based methods while accounting for sample errors. Additionally, the book provides detailed descriptions of new developments and a diverse range of approaches to address common challenges. This book is designed for graduate and advanced level students, researchers, and practitioners alike.

“Advanced Ranked Set Sampling Theory with Auxiliary Information” Book Review: The book integrates various sources of information, such as professional knowledge, auxiliary information, and judgement, with simple random sampling. It also provides detailed discussions of the properties of ranked set sampling and stratified ranked set sampling, with empirical studies to illustrate their application. Additionally, the book showcases the use of auxiliary information to enhance the efficiency of estimators for population parameters. It demonstrates how to formulate estimators for population mean by leveraging auxiliary information in ranked set sampling and stratified ranked set sampling.

“Sampling Theory and Testing Hypothesis” Book Review: This book provides a comprehensive overview of the developments in sampling theory and hypothesis testing, as well as their applications in various disciplines dealing with statistical analysis. It covers key issues related to sampling theory and hypothesis testing. The book is an ideal resource for biologists, statisticians, and operational researchers.

“Sampling Theory for Forest Inventory: A Teach-Yourself Course” Book Review: The book presents a comprehensive overview of sampling techniques employed in forest inventory. It outlines how large-scale data on forest areas are commonly collected through sampling and provides guidance on selecting the most appropriate method based on the specific field and financial considerations. Additionally, the book details the process of condensing the extensive data collected during the sampling procedure into manageable representative quantities.

“Categorical Data Analysis” Book Review: This book offers a comprehensive discussion of generalized linear models, connecting logistic regression and Poisson and negative binomial log-linear models. It covers logistic and probit regression methods for binary, ordinal, and nominal responses, and includes alternative methods for binary response data, smoothing, and regularization. Additionally, it presents classification methods such as linear discriminant analysis, classification trees, and cluster analysis. With more than 100 data set analyses and over 600 practice exercises, this book is an ideal resource for statisticians and methodologists.

“Regression Analysis – Theory, Methods and Applications” Book Review: This comprehensive book covers both the theory and methods of regression analysis, as well as its applications in real-life scenarios. It provides a solid foundation in the theory of this important subject and includes numerous numerical and example problems for readers to practice. Additionally, the book features nonparametric methods that can be utilized by both statisticians and practitioners.

“Practical Nonparametric Statistics” Book Review: This book provides a comprehensive guide to nonparametric statistical methods, with a focus on practical applications. The book covers a wide range of topics, including one- and two-sample problems, analysis of variance, regression analysis, and categorical data analysis. Conover’s clear writing style and numerous examples make the material accessible to readers with a basic understanding of statistics.

“Nonparametric Methods in Quantitative Analysis” Book Review: This book is based on recent research investigations that have been published in social science journals. It includes a detailed discussion of the specific methodology and logical rationale of nonparametric methods that can be applied to both small and large sample sizes. The methods are organized according to the type of sample structure. Additionally, the book covers location tests such as the sign test, the Mann-Whitney-Wilcoxon test, the Kruskal-Wallis test, and Friedman’s test. With its accessible language and clear explanations, this book is an ideal resource for undergraduate students.

“Nonparametric Statistical Methods” Book Review: This updated and revised book includes modern topics and procedures of nonparametric methods, as well as more practical data sets and new problems derived from real-life situations. It emphasizes the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the technical skills needed to apply the appropriate procedures for any situation.

“Sampling Theory: Beyond Bandlimited Systems” Book Review: The book is an ideal resource for students of statistics taking a course on sample survey methodology, as well as survey statisticians and practitioners. It presents a comprehensive overview of classical techniques of survey sampling, as well as the prediction-theoretic approach to survey sampling and methods for addressing nonsampling errors. The book includes coverage of nonparametric variance estimation methods, analysis of complex surveys, and concepts related to unequal probability sampling. Additionally, the book provides detailed discussions of nonsampling errors, including Randomised Response Techniques. Over 70 worked-out examples and more than 120 problems and solutions are included to facilitate learning and application of the material.

“Recent Advances in Sampling Theory” Book Review: This is an informative book that covers all aspects of sampling theory, from its history to modern-day developments. The book is designed for students and professionals in the field of statistics, providing a comprehensive overview of the topic with easy-to-understand explanations and examples. The authors use clear language and organize the book in a logical manner, making it easy to follow along.

“Sampling Theory And Methods” Book Review: This is an informative book that covers a wide range of topics related to sampling theory. It is designed for advanced level students, researchers, and practitioners. The book provides a detailed introduction to the fundamentals of sampling theory and practical applications, as well as an overview of survey sampling. The author also presents the latest research and cutting-edge methods in survey sampling, making it a valuable resource for those looking to keep up with current trends in the field. With clear explanations and numerous examples, this book is a useful guide for anyone interested in sampling theory and methods.