Modern Mathematical Statistics With Applications
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Modern Mathematical Statistics With Applications
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Author : Jay L. Devore
language : en
Publisher: Springer Nature
Release Date : 2021-04-29
Modern Mathematical Statistics With Applications written by Jay L. Devore and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Mathematics categories.
This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear and current exposition of statistical concepts and methodology, including many examples and exercises based on real data gleaned from publicly available sources. Here is a small but representative selection of scenarios for our examples and exercises based on information in recent articles: Use of the “Big Mac index” by the publication The Economist as a humorous way to compare product costs across nations Visualizing how the concentration of lead levels in cartridges varies for each of five brands of e-cigarettes Describing the distribution of grip size among surgeons and how it impacts their ability to use a particular brand of surgical stapler Estimating the true average odometer reading of used Porsche Boxsters listed for sale on www.cars.com Comparing head acceleration after impact when wearing a football helmet with acceleration without a helmet Investigating the relationship between body mass index and foot load while running The main focus of the book is on presenting and illustrating methods of inferential statistics used by investigators in a wide variety of disciplines, from actuarial science all the way to zoology. It begins with a chapter on descriptive statistics that immediately exposes the reader to the analysis of real data. The next six chapters develop the probability material that facilitates the transition from simply describing data to drawing formal conclusions based on inferential methodology. Point estimation, the use of statistical intervals, and hypothesis testing are the topics of the first three inferential chapters. The remainder of the book explores the use of these methods in a variety of more complex settings. This edition includes many new examples and exercises as well as an introduction to the simulation of events and probability distributions. There are more than 1300 exercises in the book, ranging from very straightforward to reasonably challenging. Many sections have been rewritten with the goal of streamlining and providing a more accessible exposition. Output from the most common statistical software packages is included wherever appropriate (a feature absent from virtually all other mathematical statistics textbooks). The authors hope that their enthusiasm for the theory and applicability of statistics to real world problems will encourage students to pursue more training in the discipline.
Devore Berk S Modern Mathematical Statistics With Applications
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Author : Matthew A. Carlton
language : en
Publisher: Duxbury Press
Release Date : 2006-01-03
Devore Berk S Modern Mathematical Statistics With Applications written by Matthew A. Carlton and has been published by Duxbury Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-03 with Mathematics categories.
The Student Solutions Manual provides worked-out solutions to the selected problems in the text.
Modern Mathematical Statistics With Applications
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Author : Canaan Knight
language : en
Publisher: Larsen and Keller Education
Release Date : 2023-09-19
Modern Mathematical Statistics With Applications written by Canaan Knight and has been published by Larsen and Keller Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-19 with Mathematics categories.
Statistics is a branch of applied mathematics that deals with collecting, describing, presenting and analyzing data. It also involves making inferences or conclusions from the given quantitative data. There are two major areas of statistics, namely, descriptive statistics and inferential statistics. Descriptive statistics is focused on describing the properties associated with the sample and population data. In inferential statistics, sample data is analyzed to test hypotheses and draw conclusions. Some of the common and widely used statistical tools and procedures are variance, skewness, linear regression analysis, null hypothesis testing, probit models, ANOVA, and mean. Statistics and statistical techniques draw heavily on various mathematical theories such as differential and integral calculus, linear algebra, and probability theory. Statistics finds applications in a variety of disciplines and professions including economics and finance, accounting, academic research, and investment analysis. The book studies, and analyzes mathematical statistics and its applications in modern times. It is an essential guide for both academicians and those who wish to pursue this discipline further.
Basics Of Modern Mathematical Statistics
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Author : Wolfgang Karl Härdle
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-08
Basics Of Modern Mathematical Statistics written by Wolfgang Karl Härdle 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 2013-11-08 with Mathematics categories.
The complexity of today’s statistical data calls for modern mathematical tools. Many fields of science make use of mathematical statistics and require continuous updating on statistical technologies. Practice makes perfect, since mastering the tools makes them applicable. Our book of exercises and solutions offers a wide range of applications and numerical solutions based on R. In modern mathematical statistics, the purpose is to provide statistics students with a number of basic exercises and also an understanding of how the theory can be applied to real-world problems. The application aspect is also quite important, as most previous exercise books are mostly on theoretical derivations. Also we add some problems from topics often encountered in recent research papers. The book was written for statistics students with one or two years of coursework in mathematical statistics and probability, professors who hold courses in mathematical statistics, and researchers in other fields who would like to do some exercises on math statistics.
Classic Topics On The History Of Modern Mathematical Statistics
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Author : Prakash Gorroochurn
language : en
Publisher: John Wiley & Sons
Release Date : 2016-04-04
Classic Topics On The History Of Modern Mathematical Statistics written by Prakash Gorroochurn 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 2016-04-04 with Mathematics categories.
"There is nothing like it on the market...no others are as encyclopedic...the writing is exemplary: simple, direct, and competent." —George W. Cobb, Professor Emeritus of Mathematics and Statistics, Mount Holyoke College Written in a direct and clear manner, Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times presents a comprehensive guide to the history of mathematical statistics and details the major results and crucial developments over a 200-year period. Presented in chronological order, the book features an account of the classical and modern works that are essential to understanding the applications of mathematical statistics. Divided into three parts, the book begins with extensive coverage of the probabilistic works of Laplace, who laid much of the foundations of later developments in statistical theory. Subsequently, the second part introduces 20th century statistical developments including work from Karl Pearson, Student, Fisher, and Neyman. Lastly, the author addresses post-Fisherian developments. Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times also features: A detailed account of Galton's discovery of regression and correlation as well as the subsequent development of Karl Pearson's X2 and Student's t A comprehensive treatment of the permeating influence of Fisher in all aspects of modern statistics beginning with his work in 1912 Significant coverage of Neyman–Pearson theory, which includes a discussion of the differences to Fisher’s works Discussions on key historical developments as well as the various disagreements, contrasting information, and alternative theories in the history of modern mathematical statistics in an effort to provide a thorough historical treatment Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times is an excellent reference for academicians with a mathematical background who are teaching or studying the history or philosophical controversies of mathematics and statistics. The book is also a useful guide for readers with a general interest in statistical inference.
Modern Mathematical Statistics
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Author : Edward J. Dudewicz
language : en
Publisher:
Release Date : 1988-01-18
Modern Mathematical Statistics written by Edward J. Dudewicz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-01-18 with Mathematics categories.
This text covers the science of statistics. In addition to classical probability theory, such topics as order statistics and limiting distributions are discussed, along with applied examples from a wide variety of fields.
Basics Of Modern Mathematical Statistics
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Author : Vladimir Spokoiny
language : en
Publisher: Springer
Release Date : 2014-10-25
Basics Of Modern Mathematical Statistics written by Vladimir Spokoiny and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-25 with Mathematics categories.
This textbook provides a unified and self-contained presentation of the main approaches to and ideas of mathematical statistics. It collects the basic mathematical ideas and tools needed as a basis for more serious study or even independent research in statistics. The majority of existing textbooks in mathematical statistics follow the classical asymptotic framework. Yet, as modern statistics has changed rapidly in recent years, new methods and approaches have appeared. The emphasis is on finite sample behavior, large parameter dimensions, and model misspecifications. The present book provides a fully self-contained introduction to the world of modern mathematical statistics, collecting the basic knowledge, concepts and findings needed for doing further research in the modern theoretical and applied statistics. This textbook is primarily intended for graduate and postdoc students and young researchers who are interested in modern statistical methods.
Modern Concepts And Theorems Of Mathematical Statistics
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Author : Edward B. Manoukian
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Modern Concepts And Theorems Of Mathematical Statistics written by Edward B. Manoukian 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 2012-12-06 with Mathematics categories.
With the rapid progress and development of mathematical statistical methods, it is becoming more and more important for the student, the in structor, and the researcher in this field to have at their disposal a quick, comprehensive, and compact reference source on a very wide range of the field of modern mathematical statistics. This book is an attempt to fulfill this need and is encyclopedic in nature. It is a useful reference for almost every learner involved with mathematical statistics at any level, and may supple ment any textbook on the subject. As the primary audience of this book, we have in mind the beginning busy graduate student who finds it difficult to master basic modern concepts by an examination of a limited number of existing textbooks. To make the book more accessible to a wide range of readers I have kept the mathematical language at a level suitable for those who have had only an introductory undergraduate course on probability and statistics, and basic courses in calculus and linear algebra. No sacrifice, how ever, is made to dispense with rigor. In stating theorems I have not always done so under the weakest possible conditions. This allows the reader to readily verify if such conditions are indeed satisfied in most applications given in modern graduate courses without being lost in extra unnecessary mathematical intricacies. The book is not a mere dictionary of mathematical statistical terms.
Mathematical Statistics With Applications In R
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Author : Kandethody M. Ramachandran
language : en
Publisher: Elsevier
Release Date : 2014-09-14
Mathematical Statistics With Applications In R written by Kandethody M. Ramachandran and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-14 with Mathematics categories.
Mathematical Statistics with Applications in R, Second 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 the 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. This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students. Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. 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 Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods
Probability And Mathematical Statistics Theory Applications And Practice In R
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Author : Mary C. Meyer
language : en
Publisher: SIAM
Release Date : 2019-06-24
Probability And Mathematical Statistics Theory Applications And Practice In R written by Mary C. Meyer and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-24 with Mathematics categories.
This book develops the theory of probability and mathematical statistics with the goal of analyzing real-world data. Throughout the text, the R package is used to compute probabilities, check analytically computed answers, simulate probability distributions, illustrate answers with appropriate graphics, and help students develop intuition surrounding probability and statistics. Examples, demonstrations, and exercises in the R programming language serve to reinforce ideas and facilitate understanding and confidence. The book’s Chapter Highlights provide a summary of key concepts, while the examples utilizing R within the chapters are instructive and practical. Exercises that focus on real-world applications without sacrificing mathematical rigor are included, along with more than 200 figures that help clarify both concepts and applications. In addition, the book features two helpful appendices: annotated solutions to 700 exercises and a Review of Useful Math. Written for use in applied masters classes, Probability and Mathematical Statistics: Theory, Applications, and Practice in R is also suitable for advanced undergraduates and for self-study by applied mathematicians and statisticians and qualitatively inclined engineers and scientists.