The Theory of Probability is a major tool that can be used to explain and understand the various phenomena in different natural, physical and social sciences. This book provides a systematic exposition of the theory in a setting which contains a balanced mixture of the classical approach and the modern day axiomatic approach. After reviewing the basis of the theory, the book considers univariate distributions, bivariate normal distribution, multinomial distribution and convergence of random variables. Difficult ideas have been explained lucidly and have been augmented with explanatory notes, examples and exercises. The basic requirement for reading this book is simply a knowledge of mathematics at graduate level. This book tries to explain the difficult ideas in the axiomatic approach to the theory of probability in a clear and comprehensible manner. It includes several unusual distributions including the power series distribution that have been covered in great detail. Readers will find many worked-out examples and exercises with hints, which will make the book easily readable and engaging. The author is a former Professor of the Indian Statistical Institute, India.
This is a comprehensive exposition of survey sampling useful both to the students of statistics for the course on sample survey and to the survey statisticians and practitioners involved in consultancy services, marketing, opinion polls, and so on. The text offers updated review of difficult classical techniques of survey sampling, besides covering prediction-theoretic approach of survey sampling and nonsampling errors. NEW TO THIS EDITION Two new chapters—Nonparametric Methods of Variance Estimation (Chapter 19) and Analysis of Complex Surveys (Chapter 20)—have been added. These would greatly benefit the readers. KEY FEATURES Covers concepts of unequal probability sampling. Provides problems of making inference from finite population using tools of classical inference. Describes nonsampling errors including Randomised Response Techniques. Gives over 70 worked-out examples and more than 120 problems and solutions. Supplies live data from India and Sweden—in examples and exercises. What the Reviewer says: This is a very comprehensive modern text on survey sampling with a strong slant towards theoretical results. The book is an excellent reference book and would be a good graduate level sampling text for a course with an emphasis on sampling theory. — JESSE C. ARNOLD, Virginia Polytechnic Institute and State University
This textbook presents a classical approach to some techniques of multivariate analysis in a simple and transparent manner. It offers clear and concise development of the concepts; interpretation of the output of the analysis; and criteria for selection of the methods, taking into account the strengths and weaknesses of each. With its roots in matrix algebra, for which a separate chapter has been added as an appendix, the book includes both data-oriented techniques and a reasonable coverage of classical methods supplemented by comments about robustness and general practical applicability. It also illustrates the methods of numerical calculations at various stages.This self-contained book is ideal as an advanced textbook for graduate students in statistics and other disciplines like social, biological and physical sciences. It will also be of benefit to professional statisticians.The author is a former Professor of the Indian Statistical Institute, India.
This Book Provides A Comprehensive Account Of Survey Sampling Theory In Fixed Population Approach And Model Based Approach. After Making A Critical Review Of Different Results In Fixed Population Set Up It Shows How Super Population Models Can Be Exploited To Produce Optimal And Robust Sampling Strategies, Specially In Large Scale Sample Surveys. The Central Theme Of The Book Is The Use Of Super Population Models In Making Inference From Sample Surveys. The Book Also Gives Suitable Emphasis On Different Practical Aspects, Like Choice Of Sampling Designs, Variance Estimation, Different Replication And Resampling Procedures.The Author Has Taken Care To Presuppose Nothing More On The Part Of The Reader Than A First Course In Statistical Inference, Sampling Theory And Regression Analysis. He Has Systematically Arranged The Main Results, Supplied Short Proofs, Examples, Explanatory Notes And Remarks And Indicated Research Areas. The Book Will Be Very Useful To Researchers. The Survey Practitioners Will Also Find Some Part Of The Book Very Helpful.
This book is an attempt to present an integrated and unified approach to the analysis of FRP composite materials which have a wide range of applications in various engineering structures- offshore, maritime, aerospace and civil engineering; machine components; chemical engineering applications, and so on.
This textbook is the student edition of the work on vibrations, dynamics and structural systems. There are exercises included at the end of each chapter.
This textbook has been primarily written for undergraduate and postgraduate engineering students studying the mechanics of solids and structural systems. The content focuses on matrix, finite elements, structural analysis, and computer implementation in a unified and integrated manner. Using classical methods of structural analysis, it discusses matrix and the finite element methods in an easy-to-understand manner. It consists of a large number of diagrams and illustrations for easy understanding of the concepts. All the computer codes are presented in "FORTRAN" AND "C". This textbook is highly useful for the undergraduate and postgraduate engineering students. It also acquaints the practicing engineers about the computer-based techniques used in structural analysis.
This book introduces the theory of structural dynamics, with focus on civil engineering structures. It presents modern methods of analysis and techniques adaptable to computer programming clearly and easily. The book is ideal as a text for advanced undergraduates or graduate students taking a first course in structural dynamics. It is arranged in such a way that it can be used for a one- or two-semester course, or span the undergraduate and graduate levels. In addition, this book serves the practicing engineer as a primary reference. This book is organized by the type of structural modeling. The author simplifies the subject by presenting a single degree-of-freedom system in the first chapters and then moves to systems with many degrees-of-freedom in the following chapters. Many worked examples/problems are presented to explain the text, and a few computer programs are presented to help better understand the concepts. The book is useful to the research scholars and professional engineers, besides senior undergraduate and postgraduate students.
This book explores the impact of railways on colonial Indian society from the commencement of railway operations in the mid-nineteenth to the early decades of the twentieth century. The book represents a historiographical departure. Using new archival evidence as well as travelogues written by Indian railway travellers in Bengali and Hindi, this book suggests that the impact of railways on colonial Indian society were more heterogeneous and complex than anticipated either by India’s colonial railway builders or currently assumed by post-colonial scholars. At a related level, the book argues that this complex outcome of the impact of railways on colonial Indian society was a product of the interaction between the colonial context of technology transfer and the Indian railway passengers who mediated this process at an everyday level. In other words, this book claims that the colonised ‘natives’ were not bystanders in this process of imposition of an imperial technology from above. On the contrary, Indians, both as railway passengers and otherwise influenced the nature and the direction of the impact of an oft-celebrated ‘tool of Empire’. The historiographical departures suggested in the book are based on examining railway spaces as social spaces – a methodological index influenced by Henri Lefebvre’s idea of social spaces as means of control, domination and power.
The primary objective of this book is to study some of the research topics in the area of analysis of complex surveys which have not been covered in any book yet. It discusses the analysis of categorical data using three models: a full model, a log-linear model and a logistic regression model. It is a valuable resource for survey statisticians and practitioners in the field of sociology, biology, economics, psychology and other areas who have to use these procedures in their day-to-day work. It is also useful for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. The importance of sample surveys today cannot be overstated. From voters’ behaviour to fields such as industry, agriculture, economics, sociology, psychology, investigators generally resort to survey sampling to obtain an assessment of the behaviour of the population they are interested in. Many large-scale sample surveys collect data using complex survey designs like multistage stratified cluster designs. The observations using these complex designs are not independently and identically distributed – an assumption on which the classical procedures of inference are based. This means that if classical tests are used for the analysis of such data, the inferences obtained will be inconsistent and often invalid. For this reason, many modified test procedures have been developed for this purpose over the last few decades.
This is a comprehensive exposition of survey sampling useful both to the students of statistics for the course on sample survey and to the survey statisticians and practitioners involved in consultancy services, marketing, opinion polls, and so on. The text offers updated review of difficult classical techniques of survey sampling, besides covering prediction-theoretic approach of survey sampling and nonsampling errors. NEW TO THIS EDITION Two new chapters—Nonparametric Methods of Variance Estimation (Chapter 19) and Analysis of Complex Surveys (Chapter 20)—have been added. These would greatly benefit the readers. KEY FEATURES Covers concepts of unequal probability sampling. Provides problems of making inference from finite population using tools of classical inference. Describes nonsampling errors including Randomised Response Techniques. Gives over 70 worked-out examples and more than 120 problems and solutions. Supplies live data from India and Sweden—in examples and exercises. What the Reviewer says: This is a very comprehensive modern text on survey sampling with a strong slant towards theoretical results. The book is an excellent reference book and would be a good graduate level sampling text for a course with an emphasis on sampling theory. — JESSE C. ARNOLD, Virginia Polytechnic Institute and State University
This textbook presents a classical approach to some techniques of multivariate analysis in a simple and transparent manner. It offers clear and concise development of the concepts; interpretation of the output of the analysis; and criteria for selection of the methods, taking into account the strengths and weaknesses of each." "This book is ideal as an advanced textbook for graduate students in statistics and other disciplines like social, biological and physical sciences. It will also be of benefit to professional statisticians." --Book Jacket.
Survey Sampling reviews aspects of statistical inference in finite population sampling. After reviewing important results in fixed population models, the book considers in detail the model-dependent optimal strategies of Royall and Herson (1973) and the robustification of these strategies under model breakdown. It then reviews model assist strategies of Cassel, Sarndal and Wretman (1976) and Wright (1983). Asymptotic properties of these strategies are also reviewed. Another approach is design-based calibration of Deville and Sarndal (1992). Design-based conditional inference is an alternative approach which has drawn considerable attention to survey statisticians. Lastly the book reviews two important tools of making inference, -Model Calibration approach and Empirical Likelihood based approach. Post-stratification is another aspect which requires considerable attention.
The theory of estimating functions plays a major role in analysis of data pertaining to Biostatistics, Econometrics, Time Series Analysis, Reliability studies and other varied fields. This book discusses at length the application of the theory in interpretation of results in Survey Sampling.
The Theory of Probability is a major tool that can be used to explain and understand the various phenomena in different natural, physical and social sciences. This book provides a systematic exposition of the theory in a setting which contains a balanced mixture of the classical approach and the modern day axiomatic approach. After reviewing the basis of the theory, the book considers univariate distributions, bivariate normal distribution, multinomial distribution, convergence of random variables and elements of stochastic process. Difficult ideas have been explained lucidly and augmented with explanatory notes, examples and exercises. The basic requirement for reading the book is the knowledge of mathematics at graduate level.This book tries to explain the difficult ideas in axiomatic approach to the theory in a clear and comprehensive manner. It addresses several unusual distributions including the power series distribution. Readers will find many worked-out examples and exercises with hints, which will make the book easily readable and engaging.The author is a former professor of the Indian Statistical Institute, India.
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