Estimation And Inferential Statistics

Author : Pradip Kumar Sahu,Santi Ranjan Pal,Ajit Kumar Das
Publisher : Springer
Page : 317 pages
File Size : 50,7 Mb
Release : 2015-11-03
Category : Mathematics
ISBN : 9788132225140

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Estimation and Inferential Statistics by Pradip Kumar Sahu,Santi Ranjan Pal,Ajit Kumar Das Pdf

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 : Halbert White
Publisher : Cambridge University Press
Page : 396 pages
File Size : 54,9 Mb
Release : 1996-06-28
Category : Business & Economics
ISBN : 0521574463

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Estimation, Inference and Specification Analysis by Halbert White Pdf

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 : Malcolm O. Asadoorian,Demetrius Kantarelis
Publisher : University Press of America
Page : 304 pages
File Size : 52,9 Mb
Release : 2005
Category : Business & Economics
ISBN : 0761830308

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Essentials of Inferential Statistics by Malcolm O. Asadoorian,Demetrius Kantarelis Pdf

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 : Geoff Cumming,Robert Calin-Jageman
Publisher : Taylor & Francis
Page : 611 pages
File Size : 46,5 Mb
Release : 2024-03-21
Category : Psychology
ISBN : 9781003849018

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Introduction to the New Statistics by Geoff Cumming,Robert Calin-Jageman Pdf

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
Page : 568 pages
File Size : 54,6 Mb
Release : 2021-07-19
Category : Electronic
ISBN : 1532721072

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Research Decisions and Estimation With Confidence and Power by L E MacCarter Pdf

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,Hiroyuki Shioya,Chanseok Park
Publisher : CRC Press
Page : 424 pages
File Size : 46,6 Mb
Release : 2011-06-22
Category : Computers
ISBN : 9781420099669

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Statistical Inference by Ayanendranath Basu,Hiroyuki Shioya,Chanseok Park Pdf

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 : Sharmishtha Kulkarni Ph D,Anjali Upadhye Ph D
Publisher : Unknown
Page : 254 pages
File Size : 46,8 Mb
Release : 2020-11-11
Category : Electronic
ISBN : 9798562530455

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Statistical Inference by Sharmishtha Kulkarni Ph D,Anjali Upadhye Ph D Pdf

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

Author : Yoel Haitovsky,Hans Rudolf Lerche,Ya'acov Ritov
Publisher : Springer Science & Business Media
Page : 230 pages
File Size : 51,8 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9783642574108

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Foundations of Statistical Inference by Yoel Haitovsky,Hans Rudolf Lerche,Ya'acov Ritov Pdf

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 : Katarzyna Stapor
Publisher : Springer Nature
Page : 163 pages
File Size : 45,7 Mb
Release : 2020-05-22
Category : Mathematics
ISBN : 9783030457990

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Introduction to Probabilistic and Statistical Methods with Examples in R by Katarzyna Stapor Pdf

This book strikes a healthy balance between theory and applications, ensuring that it doesn’t offer a set of tools with no mathematical roots. It is intended as a comprehensive and largely self-contained introduction to probability and statistics for university students from various faculties, with accompanying implementations of some rudimentary statistical techniques in the language R. The content is divided into three basic parts: the first includes elements of probability theory, the second introduces readers to the basics of descriptive and inferential statistics (estimation, hypothesis testing), and the third presents the elements of correlation and linear regression analysis. Thanks to examples showing how to approach real-world problems using statistics, readers will acquire stronger analytical thinking skills, which are essential for analysts and data scientists alike.

Author : Bradley Efron
Publisher : Cambridge University Press
Page : 128 pages
File Size : 42,5 Mb
Release : 2012-11-29
Category : Mathematics
ISBN : 9781139492133

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Large-Scale Inference by Bradley Efron Pdf

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 : Daniel Navarro
Publisher : Lulu.com
Page : 617 pages
File Size : 42,7 Mb
Release : 2013-01-13
Category : Psychology
ISBN : 9781326189723

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Learning Statistics with R by Daniel Navarro Pdf

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

Author : Larry Wasserman
Publisher : Springer Science & Business Media
Page : 446 pages
File Size : 48,8 Mb
Release : 2013-12-11
Category : Mathematics
ISBN : 9780387217369

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All of Statistics by Larry Wasserman Pdf

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Author : Shelemyahu Zacks
Publisher : John Wiley & Sons
Page : 640 pages
File Size : 48,7 Mb
Release : 1971
Category : Mathematics
ISBN : UCAL:B4407213

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The Theory of Statistical Inference by Shelemyahu Zacks Pdf

Synopsis; Sufficient statistics; Unbiased estimation; The efficiency of estimators under quadratic loss; Maximum likelihood estimation; Bayes and minimax estimation; Equivariant estimators; Admissibility of estimators; Confidence and tolerance intervals.

Author : Kamala Singh Kushwaha
Publisher : Unknown
Page : 128 pages
File Size : 43,6 Mb
Release : 2016
Category : Electronic
ISBN : 9389547598

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Inferential Statistics by Kamala Singh Kushwaha Pdf

Author : MANOJ KUMAR SRIVASTAVA,ABDUL HAMID KHAN,NAMITA SRIVASTAVA
Publisher : PHI Learning Pvt. Ltd.
Page : 817 pages
File Size : 43,5 Mb
Release : 2014-04-03
Category : Mathematics
ISBN : 9788120349308

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STATISTICAL INFERENCE : THEORY OF ESTIMATION by MANOJ KUMAR SRIVASTAVA,ABDUL HAMID KHAN,NAMITA SRIVASTAVA Pdf

This book is sequel to a book Statistical Inference: Testing of Hypotheses (published by PHI Learning). Intended for the postgraduate students of statistics, it introduces the problem of estimation in the light of foundations laid down by Sir R.A. Fisher (1922) and follows both classical and Bayesian approaches to solve these problems. The book starts with discussing the growing levels of data summarization to reach maximal summarization and connects it with sufficient and minimal sufficient statistics. The book gives a complete account of theorems and results on uniformly minimum variance unbiased estimators (UMVUE)—including famous Rao and Blackwell theorem to suggest an improved estimator based on a sufficient statistic and Lehmann-Scheffe theorem to give an UMVUE. It discusses Cramer-Rao and Bhattacharyya variance lower bounds for regular models, by introducing Fishers information and Chapman, Robbins and Kiefer variance lower bounds for Pitman models. Besides, the book introduces different methods of estimation including famous method of maximum likelihood and discusses large sample properties such as consistency, consistent asymptotic normality (CAN) and best asymptotic normality (BAN) of different estimators. Separate chapters are devoted for finding Pitman estimator, among equivariant estimators, for location and scale models, by exploiting symmetry structure, present in the model, and Bayes, Empirical Bayes, Hierarchical Bayes estimators in different statistical models. Systematic exposition of the theory and results in different statistical situations and models, is one of the several attractions of the presentation. Each chapter is concluded with several solved examples, in a number of statistical models, augmented with exposition of theorems and results. KEY FEATURES • Provides clarifications for a number of steps in the proof of theorems and related results., • Includes numerous solved examples to improve analytical insight on the subject by illustrating the application of theorems and results. • Incorporates Chapter-end exercises to review student’s comprehension of the subject. • Discusses detailed theory on data summarization, unbiased estimation with large sample properties, Bayes and Minimax estimation, separately, in different chapters.