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Author: Pradip Kumar Sahu
Publisher: Springer
ISBN: 8132225147
Category : Mathematics
Languages : en
Pages : 317
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Book Description
This book focuses on the meaning of statistical inference and estimation. Statistical inference is concerned with the problems of estimation of population parameters and testing hypotheses. Primarily aimed at undergraduate and postgraduate students of statistics, the book is also useful to professionals and researchers in statistical, medical, social and other disciplines. It discusses current methodological techniques used in statistics and related interdisciplinary areas. Every concept is supported with relevant research examples to help readers to find the most suitable application. Statistical tools have been presented by using real-life examples, removing the “fear factor” usually associated with this complex subject. The book will help readers to discover diverse perspectives of statistical theory followed by relevant worked-out examples. Keeping in mind the needs of readers, as well as constantly changing scenarios, the material is presented in an easy-to-understand form.
Author: Pradip Kumar Sahu
Publisher: Springer
ISBN: 8132225147
Category : Mathematics
Languages : en
Pages : 317
Get Book
Book Description
This book focuses on the meaning of statistical inference and estimation. Statistical inference is concerned with the problems of estimation of population parameters and testing hypotheses. Primarily aimed at undergraduate and postgraduate students of statistics, the book is also useful to professionals and researchers in statistical, medical, social and other disciplines. It discusses current methodological techniques used in statistics and related interdisciplinary areas. Every concept is supported with relevant research examples to help readers to find the most suitable application. Statistical tools have been presented by using real-life examples, removing the “fear factor” usually associated with this complex subject. The book will help readers to discover diverse perspectives of statistical theory followed by relevant worked-out examples. Keeping in mind the needs of readers, as well as constantly changing scenarios, the material is presented in an easy-to-understand form.
Author: Malcolm O. Asadoorian
Publisher: University Press of America
ISBN: 9780761830306
Category : Business & Economics
Languages : en
Pages : 304
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Book Description
Essentials of Inferential Statistics, fourth edition is appropriate for a one semester first course in Applied Statistics or as a reference book for practicing researchers in a wide variety of disciplines, including medicine, natural and social sciences, law, and engineering. Most importantly, this practical book thoroughly describes the Bayesian principles necessary for applied clinical research and strategic interaction, which are frequently omitted in other texts. After a comprehensive treatment of probability theory concepts, theorems, and some basic proofs, this laconically written text illustrates sampling distributions and their importance in estimation for the purpose of statistical inference. The book then shifts its focus to the essentials associated with confidence intervals, and hypothesis testing for major population parameters, namely, the population mean, population variance, and population proportion. In addition, it thoroughly describes the basics of correlation and simple linear regression as well as non-parametric statistics.
Author: Halbert White
Publisher: Cambridge University Press
ISBN: 9780521574464
Category : Business & Economics
Languages : en
Pages : 396
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Book Description
This book examines the consequences of misspecifications for the interpretation of likelihood-based methods of statistical estimation and interference. The analysis concludes with an examination of methods by which the possibility of misspecification can be empirically investigated.
Author: Yoel Haitovsky
Publisher: Springer Science & Business Media
ISBN: 3642574106
Category : Mathematics
Languages : en
Pages : 230
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Book Description
This volume is a collection of papers presented at a conference held in Shoresh Holiday Resort near Jerusalem, Israel, in December 2000 organized by the Israeli Ministry of Science, Culture and Sport. The theme of the conference was "Foundation of Statistical Inference: Applications in the Medical and Social Sciences and in Industry and the Interface of Computer Sciences". The following is a quotation from the Program and Abstract booklet of the conference. "Over the past several decades, the field of statistics has seen tremendous growth and development in theory and methodology. At the same time, the advent of computers has facilitated the use of modern statistics in all branches of science, making statistics even more interdisciplinary than in the past; statistics, thus, has become strongly rooted in all empirical research in the medical, social, and engineering sciences. The abundance of computer programs and the variety of methods available to users brought to light the critical issues of choosing models and, given a data set, the methods most suitable for its analysis. Mathematical statisticians have devoted a great deal of effort to studying the appropriateness of models for various types of data, and defining the conditions under which a particular method work. " In 1985 an international conference with a similar title* was held in Is rael. It provided a platform for a formal debate between the two main schools of thought in Statistics, the Bayesian, and the Frequentists.
Author: Bradley Efron
Publisher: Cambridge University Press
ISBN: 1139492136
Category : Mathematics
Languages : en
Pages :
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Book Description
We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples.
Author: Geoff Cumming
Publisher: Taylor & Francis
ISBN: 1003849016
Category : Psychology
Languages : en
Pages : 611
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Book Description
This fully revised and updated second edition is an essential introduction to inferential statistics. It is the first introductory statistics text to use an estimation approach from the start and also to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. The estimation approach, with meta-analysis (“the new statistics”), is exactly what’s needed for Open Science. Key features of this new edition include: Even greater prominence for Open Science throughout the book. Students easily understand basic Open Science practices and are guided to use them in their own work. There is discussion of the latest developments now being widely adopted across science and medicine. Integration of new open-source esci (Estimation Statistics with Confidence Intervals) software, running in jamovi. This is ideal for the book and extends seamlessly to what’s required for more advanced courses, and also by researchers. See www.thenewstatistics.com/itns/esci/jesci/. Colorful interactive simulations, including the famous dances, to help make key statistical ideas intuitive. These are now freely available through any browser. See www.esci.thenewstatistics.com/. Coverage of both estimation and null hypothesis significance testing (NHST) approaches, with full guidance on how to translate between the two. Effective learning strategies and pedagogical features to promote critical thinking, comprehension and retention Designed for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences, researchers interested in understanding Open Science and the new statistics will also appreciate this book. No familiarity with introductory statistics is assumed.
Author: L E MacCarter
Publisher: Createspace Independent Publishing Platform
ISBN: 9781532721076
Category :
Languages : en
Pages : 568
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Book Description
Research Decisions and Estimation with Confidence and Power: This book is about research with an emphasis on inference, sample size, confidence intervals, and a rational approach to power, offered at an affordable price for students everywhere. It explores current controversies in inferential statistics. It deals with sample size estimation for a wide variety of experimental situations. An updated general statistics text/reference that emphasizes the latest approaches to a priori sample size and power Can be used as a text for majors or non-majors in statistics, as a curriculum for any level of statistical training, or as a reference for researchers 560+ pages at a price researchers and students anywhere can afford New material researched from classical and recent literature (extensive citations and index) Avoids the use of the unfortunately common "large," "medium," and "small," which has been discredited for decades, including by the tacit admission of its author, Cohen (1988, p25) Discusses ways to avoid pitfalls due to the lack of robustness of the ANOVA, the fact that data is almost never normal etc.
Author: Ayanendranath Basu
Publisher: CRC Press
ISBN: 1420099663
Category : Computers
Languages : en
Pages : 424
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Book Description
In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by "Minimum Distance Estimation" is literally huge. Filling a statistical resource gap, Stati
Author: George Casella
Publisher: CRC Press
ISBN: 1040024025
Category : Mathematics
Languages : en
Pages : 1746
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Book Description
This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and natural extensions, and consequences, of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation. Features The classic graduate-level textbook on statistical inference Develops elements of statistical theory from first principles of probability Written in a lucid style accessible to anyone with some background in calculus Covers all key topics of a standard course in inference Hundreds of examples throughout to aid understanding Each chapter includes an extensive set of graduated exercises Statistical Inference, Second Edition is primarily aimed at graduate students of statistics, but can be used by advanced undergraduate students majoring in statistics who have a solid mathematics background. It also stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures, while less focused on formal optimality considerations. This is a reprint of the second edition originally published by Cengage Learning, Inc. in 2001.
Author: Sharmishtha Kulkarni Ph D
Publisher:
ISBN:
Category :
Languages : en
Pages : 254
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Book Description
The book provides an insight into elementary inferential statistical methodologies including point estimation, interval estimation, and parametric and nonparametric tests. With a substantial emphasis on conceptual knowledge, the book provides working methodologies with sufficient number of illustrative examplesThis book focuses on the meaning of statistical inference on point estimation. Statistical inference is concerned with the problems of estimation of population parameters and testing hypotheses. Primarily aimed at undergraduate and postgraduate students of statistics, the book is also useful to professionals and researchers in statistical, medical, social and other disciplines. It discusses current methodological techniques used in statistics and related interdisciplinary areas. The book will help readers to discover diverse perspectives of statistical theory followed by relevant worked-out practical examples. Keeping in mind the needs of readers, as well as constantly changing scenarios, the material is presented in an easy-to-understand form.This book offers an accessible and comprehensive overview of statistical estimation and inference that reflects current trends in statistical research. It draws from three main themes throughout: the concepts of point estimation and properties of point estimation as unbiasedness, consistency, sufficiency, relative efficiency. They also utilize a standardized set of assumptions and tools throughout, imposing regular conditions and resulting in a more coherent and cohesive volume. Written for the graduate-level audience, this text can be used in a one-semester or two-semester course.KEY FEATURES1.Easy to understand, completely solved Problems of point estimation and its properties 2.Provides of clarification for number of steps in the proof of theorems and related results 3.Includes numerous solved examples to illustrate the application of theorems and results4.It improves the analytical insights of respondentsEvery concept is supported with relevant research examples to help readers to find the most suitable application
