Nonparametric Statistics With Applications To Science And Engineering With R


Nonparametric Statistics With Applications To Science And Engineering With R
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Nonparametric Statistics With Applications To Science And Engineering


Nonparametric Statistics With Applications To Science And Engineering
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Author : Paul H. Kvam
language : en
Publisher: John Wiley & Sons
Release Date : 2007-08-24

Nonparametric Statistics With Applications To Science And Engineering written by Paul H. Kvam and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-24 with Mathematics categories.


A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods.



Nonparametric Statistics With Applications To Science And Engineering With R


Nonparametric Statistics With Applications To Science And Engineering With R
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Author : Paul Kvam
language : en
Publisher: John Wiley & Sons
Release Date : 2022-10-06

Nonparametric Statistics With Applications To Science And Engineering With R written by Paul Kvam and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-06 with Mathematics categories.


NONPARAMETRIC STATISTICS WITH APPLICATIONS TO SCIENCE AND ENGINEERING WITH R Introduction to the methods and techniques of traditional and modern nonparametric statistics, incorporating R code Nonparametric Statistics with Applications to Science and Engineering with R presents modern nonparametric statistics from a practical point of view, with the newly revised edition including custom R functions implementing nonparametric methods to explain how to compute them and make them more comprehensible. Relevant built-in functions and packages on CRAN are also provided with a sample code. R codes in the new edition not only enable readers to perform nonparametric analysis easily, but also to visualize and explore data using R’s powerful graphic systems, such as ggplot2 package and R base graphic system. The new edition includes useful tables at the end of each chapter that help the reader find data sets, files, functions, and packages that are used and relevant to the respective chapter. New examples and exercises that enable readers to gain a deeper insight into nonparametric statistics and increase their comprehension are also included. Some of the sample topics discussed in Nonparametric Statistics with Applications to Science and Engineering with R include: Basics of probability, statistics, Bayesian statistics, order statistics, Kolmogorov–Smirnov test statistics, rank tests, and designed experiments Categorical data, estimating distribution functions, density estimation, least squares regression, curve fitting techniques, wavelets, and bootstrap sampling EM algorithms, statistical learning, nonparametric Bayes, WinBUGS, properties of ranks, and Spearman coefficient of rank correlation Chi-square and goodness-of-fit, contingency tables, Fisher exact test, MC Nemar test, Cochran’s test, Mantel–Haenszel test, and Empirical Likelihood Nonparametric Statistics with Applications to Science and Engineering with R is a highly valuable resource for graduate students in engineering and the physical and mathematical sciences, as well as researchers who need a more comprehensive, but succinct understanding of modern nonparametric statistical methods.



Nonparametric Statistical Methods


Nonparametric Statistical Methods
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Author : Myles Hollander
language : en
Publisher: John Wiley & Sons
Release Date : 2013-11-25

Nonparametric Statistical Methods written by Myles Hollander and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-25 with Mathematics categories.


Praise for the Second Edition “This book should be an essential part of the personal library of every practicing statistician.”—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.



Mathematical Statistics With Applications In R


Mathematical Statistics With Applications In R
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Author : Kandethody M. Ramachandran
language : en
Publisher: Academic Press
Release Date : 2020-05-14

Mathematical Statistics With Applications In R written by Kandethody M. Ramachandran and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-14 with Mathematics categories.


Mathematical Statistics with Applications in R, Third Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods, such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem-solving in a logical manner. Step-by-step procedure to solve real problems make the topics very accessible. Presents step-by-step procedures to solve real problems, making each topic more accessible Provides updated application exercises in each chapter, blending theory and modern methods with the use of R Includes new chapters on Categorical Data Analysis and Extreme Value Theory with Applications Wide array coverage of ANOVA, Nonparametric, Bayesian and empirical methods



Probability Statistics With R For Engineers And Scientists


Probability Statistics With R For Engineers And Scientists
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Author : Michael Akritas
language : en
Publisher: Pearson
Release Date : 2018-03-21

Probability Statistics With R For Engineers And Scientists written by Michael Akritas and has been published by Pearson this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-21 with Engineering categories.


This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearsonhighered.com/math-classics-series for a complete list of titles. This text grew out of the author's notes for a course that he has taught for many years to a diverse group of undergraduates. The early introduction to the major concepts engages students immediately, which helps them see the big picture, and sets an appropriate tone for the course. In subsequent chapters, these topics are revisited, developed, and formalized, but the early introduction helps students build a true understanding of the concepts. The text utilizes the statistical software R, which is both widely used and freely available (thanks to the Free Software Foundation). However, in contrast with other books for the intended audience, this book by Akritas emphasizes not only the interpretation of software output, but also the generation of this output. Applications are diverse and relevant, and come from a variety of fields.



All Of Nonparametric Statistics


All Of Nonparametric Statistics
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Author : Larry Wasserman
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-10

All Of Nonparametric Statistics written by Larry Wasserman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-10 with Mathematics categories.


This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. It covers a wide range of topics including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book’s dual approach includes a mixture of methodology and theory.



Nonparametric Hypothesis Testing


Nonparametric Hypothesis Testing
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Author : Stefano Bonnini
language : en
Publisher: John Wiley & Sons
Release Date : 2014-07-01

Nonparametric Hypothesis Testing written by Stefano Bonnini and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-01 with Mathematics categories.


A novel presentation of rank and permutation tests, with accessible guidance to applications in R Nonparametric testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. This book summarizes traditional rank techniques and more recent developments in permutation testing as robust tools for dealing with complex data with low sample size. Key Features: Examines the most widely used methodologies of nonparametric testing. Includes extensive software codes in R featuring worked examples, and uses real case studies from both experimental and observational studies. Presents and discusses solutions to the most important and frequently encountered real problems in different fields. Features a supporting website (www.wiley.com/go/hypothesis_testing) containing all of the data sets examined in the book along with ready to use R software codes. Nonparametric Hypothesis Testing combines an up to date overview with useful practical guidance to applications in R, and will be a valuable resource for practitioners and researchers working in a wide range of scientific fields including engineering, biostatistics, psychology and medicine.



Statistics And Probability With Applications For Engineers And Scientists Using Minitab R And Jmp


Statistics And Probability With Applications For Engineers And Scientists Using Minitab R And Jmp
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Author : Bhisham C. Gupta
language : en
Publisher: John Wiley & Sons
Release Date : 2020-02-05

Statistics And Probability With Applications For Engineers And Scientists Using Minitab R And Jmp written by Bhisham C. Gupta and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-05 with Mathematics categories.


Introduces basic concepts in probability and statistics to data science students, as well as engineers and scientists Aimed at undergraduate/graduate-level engineering and natural science students, this timely, fully updated edition of a popular book on statistics and probability shows how real-world problems can be solved using statistical concepts. It removes Excel exhibits and replaces them with R software throughout, and updates both MINITAB and JMP software instructions and content. A new chapter discussing data mining—including big data, classification, machine learning, and visualization—is featured. Another new chapter covers cluster analysis methodologies in hierarchical, nonhierarchical, and model based clustering. The book also offers a chapter on Response Surfaces that previously appeared on the book’s companion website. Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP, Second Edition is broken into two parts. Part I covers topics such as: describing data graphically and numerically, elements of probability, discrete and continuous random variables and their probability distributions, distribution functions of random variables, sampling distributions, estimation of population parameters and hypothesis testing. Part II covers: elements of reliability theory, data mining, cluster analysis, analysis of categorical data, nonparametric tests, simple and multiple linear regression analysis, analysis of variance, factorial designs, response surfaces, and statistical quality control (SQC) including phase I and phase II control charts. The appendices contain statistical tables and charts and answers to selected problems. Features two new chapters—one on Data Mining and another on Cluster Analysis Now contains R exhibits including code, graphical display, and some results MINITAB and JMP have been updated to their latest versions Emphasizes the p-value approach and includes related practical interpretations Offers a more applied statistical focus, and features modified examples to better exhibit statistical concepts Supplemented with an Instructor's-only solutions manual on a book’s companion website Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP is an excellent text for graduate level data science students, and engineers and scientists. It is also an ideal introduction to applied statistics and probability for undergraduate students in engineering and the natural sciences.



Mathematical Statistics With Applications


Mathematical Statistics With Applications
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Author : Kandethody M. Ramachandran
language : en
Publisher: Academic Press
Release Date : 2009-03-13

Mathematical Statistics With Applications written by Kandethody M. Ramachandran and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-03-13 with Mathematics categories.


Mathematical Statistics with Applications provides a calculus-based theoretical introduction to mathematical statistics while emphasizing interdisciplinary applications as well as exposure to modern statistical computational and simulation concepts that are not covered in other textbooks. Includes the Jackknife, Bootstrap methods, the EM algorithms and Markov chain Monte Carlo methods. Prior probability or statistics knowledge is not required. Step-by-step procedure to solve real problems, making the topic more accessible Exercises blend theory and modern applications Practical, real-world chapter projects Provides an optional section in each chapter on using Minitab, SPSS and SAS commands



Probability Statistics With R For Engineers And Scientists


Probability Statistics With R For Engineers And Scientists
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Author : Michael Akritas
language : en
Publisher: Pearson College Division
Release Date : 2014-12-24

Probability Statistics With R For Engineers And Scientists written by Michael Akritas and has been published by Pearson College Division this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-24 with Mathematics categories.


NOTE: This edition features the same content as the traditional text in a convenient, three-hole-punched, loose-leaf version. Books a la Carte also offer a great value this format costs significantly less than a new textbook. Before purchasing, check with your instructor or review your course syllabus to ensure that you select the correct ISBN. Several versions of Pearson's MyLab & Mastering products exist for each title, including customized versions for individual schools, and registrations are not transferable. In addition, you may need a CourseID, provided by your instructor, to register for and use Pearson's MyLab & Mastering products. This text grew out of the author s notes for a course that he has taught for many years to a diverse group of undergraduates. The early introduction to the major concepts of the courseengages students immediately, which helps them see the big picture, and sets an appropriate tone. In subsequent chapters, these topics are revisited, developed, and formalized, but the early introduction helps students build a true understanding of the concepts. The text utilizes the statistical software R, which is both widely used and freely available (thanks to the Free Software Foundation). However, in contrast with other books for the intended audience, this book by Akritas emphasizes not only the interpretation of software output, but also the generation of this output. Applications are diverse and relevant, and come from a variety of fields. "