Fundamentals Of Testing Statistical Hypotheses PDF Download
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Author: A. Santhakumaran
Publisher: Atlantic Publishers & Dist
ISBN: 9788126900442
Category :
Languages : en
Pages : 166
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Book Description
This Book Covers The Fundamentals Of Testing Of Statistical Hypotheses. It Presents The Concepts, Techniques And Applications Of Hypotheses Testing And Equips The Reader With Ability To Apply To Various Real Life Problems. The Book Is Based On The Author'S Long Experience Of Teaching The Subject.The Book Will Be Useful For Students And Teachers Of Undergraduate And Postgraduate Classes. It Will Also Be Helpful For Candidates Appearing In Competitive Examination Like Iss, Ugc, Slet Etc.Salient Features Of The Book Are :" Properly Graded And Solved Problems To Illustrate Each Concept And Procedure Are Presented In The Text." Selected Problems, University Questions And Questions, Including Those Of Objective Types, Of Various Competitive Examinations Are Added At The End Of Each Chapter." Statistical Table Values Are Obtained Using C Language." Provides Conceptual Clarity, Simplicity And Uptodate Materials.
Author: A. Santhakumaran
Publisher: Atlantic Publishers & Dist
ISBN: 9788126900442
Category :
Languages : en
Pages : 166
Get Book
Book Description
This Book Covers The Fundamentals Of Testing Of Statistical Hypotheses. It Presents The Concepts, Techniques And Applications Of Hypotheses Testing And Equips The Reader With Ability To Apply To Various Real Life Problems. The Book Is Based On The Author'S Long Experience Of Teaching The Subject.The Book Will Be Useful For Students And Teachers Of Undergraduate And Postgraduate Classes. It Will Also Be Helpful For Candidates Appearing In Competitive Examination Like Iss, Ugc, Slet Etc.Salient Features Of The Book Are :" Properly Graded And Solved Problems To Illustrate Each Concept And Procedure Are Presented In The Text." Selected Problems, University Questions And Questions, Including Those Of Objective Types, Of Various Competitive Examinations Are Added At The End Of Each Chapter." Statistical Table Values Are Obtained Using C Language." Provides Conceptual Clarity, Simplicity And Uptodate Materials.
Author: Erich L. Lehmann
Publisher: Springer Science & Business Media
ISBN: 0387227288
Category : Mathematics
Languages : en
Pages : 590
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Book Description
This second, much enlarged edition by Lehmann and Casella of Lehmann's classic text on point estimation maintains the outlook and general style of the first edition. All of the topics are updated, while an entirely new chapter on Bayesian and hierarchical Bayesian approaches is provided, and there is much new material on simultaneous estimation. Each chapter concludes with a Notes section which contains suggestions for further study. This is a companion volume to the second edition of Lehmann's "Testing Statistical Hypotheses".
Author: Rand R. Wilcox
Publisher: Academic Press
ISBN: 0127515429
Category : Mathematics
Languages : en
Pages : 610
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Book Description
This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression. It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods, placing the new methods in historical context. Author Rand Wilcox includes chapter exercises and many real-world examples that illustrate how various methods perform in different situations. Introduction to Robust Estimation and Hypothesis Testing, Second Edition, focuses on the practical applications of modern, robust methods which can greatly enhance our chances of detecting true differences among groups and true associations among variables. * Covers latest developments in robust regression * Covers latest improvements in ANOVA * Includes newest rank-based methods * Describes and illustrated easy to use software
Author: Erich L. Lehmann
Publisher: Springer Science & Business Media
ISBN: 038727605X
Category : Mathematics
Languages : en
Pages : 795
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Book Description
The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes over 300 new problems out of a total of more than 760.
Author: Kathryn Kozak
Publisher: Lulu.com
ISBN: 1329757254
Category : Education
Languages : en
Pages : 459
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Book Description
Statistics With Technology, Second Edition, is an introductory statistics textbook. It uses the TI-83/84 calculator and R, an open source statistical software, for all calculations. Other technology can also be used besides the TI-83/84 calculator and the software R, but these are the ones that are presented in the text. This book presents probability and statistics from a more conceptual approach, and focuses less on computation. Analysis and interpretation of data is more important than how to compute basic statistical values.
Author: Ning-Zhong Shi
Publisher: World Scientific
ISBN: 9812814361
Category : Science
Languages : en
Pages : 320
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Book Description
This book presents up-to-date theory and methods of statistical hypothesis testing based on measure theory. The so-called statistical space is a measurable space adding a family of probability measures. Most topics in the book will be developed based on this term. The book includes some typical data sets, such as the relation between race and the death penalty verdict, the behavior of food intake of two kinds of Zucker rats, and the per capita income and expenditure in China during the 1978?2002 period. Emphasis is given to the process of finding appropriate statistical techniques and methods of evaluating these techniques.
Author: Stefan Wellek
Publisher: CRC Press
ISBN: 9781439808191
Category : Mathematics
Languages : en
Pages : 431
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Book Description
While continuing to focus on methods of testing for two-sided equivalence, Testing Statistical Hypotheses of Equivalence and Noninferiority, Second Edition gives much more attention to noninferiority testing. It covers a spectrum of equivalence testing problems of both types, ranging from a one-sample problem with normally distributed observations
Author: Daniel Navarro
Publisher: Lulu.com
ISBN: 1326189727
Category : Computers
Languages : en
Pages : 617
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Book Description
"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: Pieter Kubben
Publisher: Springer
ISBN: 3319997130
Category : Medical
Languages : en
Pages : 219
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Book Description
This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.
Author: Rand R. Wilcox
Publisher: Springer Science & Business Media
ISBN: 1441955240
Category : Social Science
Languages : en
Pages : 255
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Book Description
Conventional statistical methods have a very serious flaw. They routinely miss differences among groups or associations among variables that are detected by more modern techniques, even under very small departures from normality. Hundreds of journal articles have described the reasons standard techniques can be unsatisfactory, but simple, intuitive explanations are generally unavailable. Situations arise where even highly nonsignificant results become significant when analyzed with more modern methods. Without assuming the reader has any prior training in statistics, Part I of this book describes basic statistical principles from a point of view that makes their shortcomings intuitive and easy to understand. The emphasis is on verbal and graphical descriptions of concepts. Part II describes modern methods that address the problems covered in Part I. Using data from actual studies, many examples are included to illustrate the practical problems with conventional procedures and how more modern methods can make a substantial difference in the conclusions reached in many areas of statistical research. The second edition of this book includes a number of advances and insights that have occurred since the first edition appeared. Included are new results relevant to medians, regression, measures of association, strategies for comparing dependent groups, methods for dealing with heteroscedasticity, and measures of effect size.
