Filename: modern-mathematical-statistics-with-applications.pdf
ISBN: 9781461403906
Release Date: 2011-12-06
Number of pages: 845
Author: Jay L. Devore
Publisher: Springer Science & Business Media

Download and read online Modern Mathematical Statistics with Applications in PDF and EPUB Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without much attention paid to how statistics is actually used.. In contrast, Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. In keeping with the recommendation that every math student should study statistics and probability with an emphasis on data analysis, accomplished authors Jay Devore and Kenneth Berk make statistical concepts and methods clear and relevant through careful explanations and a broad range of applications involving real data. The main focus of the book is on presenting and illustrating methods of inferential statistics that are useful in research. It begins with a chapter on descriptive statistics that immediately exposes the reader to real data. The next six chapters develop the probability material that bridges the gap between descriptive and inferential statistics. Point estimation, inferences based on statistical intervals, and hypothesis testing are then introduced in the next three chapters. The remainder of the book explores the use of this methodology in a variety of more complex settings. This edition includes a plethora of new exercises, a number of which are similar to what would be encountered on the actuarial exams that cover probability and statistics. Representative applications include investigating whether the average tip percentage in a particular restaurant exceeds the standard 15%, considering whether the flavor and aroma of Champagne are affected by bottle temperature or type of pour, modeling the relationship between college graduation rate and average SAT score, and assessing the likelihood of O-ring failure in space shuttle launches as related to launch temperature.

Filename: modern-mathematical-statistics-with-applications.pdf
ISBN: 9781461403913
Release Date: 2011-12-07
Number of pages: 845
Author: Jay L. Devore
Publisher: Springer Science & Business Media

Download and read online Modern Mathematical Statistics with Applications in PDF and EPUB Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. In keeping with the recommendation that every math student should study statistics and probability with an emphasis on data analysis, accomplished authors Jay Devore and Kenneth Berk make statistical concepts and methods clear and relevant through careful explanations and a broad range of applications involving real data. The main focus of the book is on presenting and illustrating methods of inferential statistics that are useful in research. It begins with a chapter on descriptive statistics that immediately exposes the reader to real data. The next six chapters develop the probability material that bridges the gap between descriptive and inferential statistics. Point estimation, inferences based on statistical intervals, and hypothesis testing are then introduced in the next three chapters. The remainder of the book explores the use of this methodology in a variety of more complex settings. This edition includes a plethora of new exercises, a number of which are similar to what would be encountered on the actuarial exams that cover probability and statistics. Representative applications include investigating whether the average tip percentage in a particular restaurant exceeds the standard 15%, considering whether the flavor and aroma of Champagne are affected by bottle temperature or type of pour, modeling the relationship between college graduation rate and average SAT score, and assessing the likelihood of O-ring failure in space shuttle launches as related to launch temperature.

Filename: modern-mathematical-statistics-with-applications.pdf
ISBN: 9780534404734
Release Date: 2007
Number of pages: 848
Author: Jay L. Devore
Publisher: Cengage Learning

Download and read online Modern Mathematical Statistics with Applications in PDF and EPUB CD-ROM contains datasets formatted for MINITAB, SAS, SPSS, JMP, Microsoft Excel, and ASCII, as well as MINITAB macros for doing bootstrapping and permutation tests.

Filename: devore-berk-s-modern-mathematical-statistics-with-applications.pdf
ISBN: 053440474X
Release Date: 2006-01-03
Number of pages: 252
Author: Matthew A. Carlton
Publisher: Duxbury Press

Download and read online Devore Berk s Modern Mathematical Statistics With Applications in PDF and EPUB The Student Solutions Manual provides worked-out solutions to the selected problems in the text.

Filename: mathematical-statistics-with-applications-in-r.pdf
ISBN: 9780124171329
Release Date: 2014-09-14
Number of pages: 826
Author: Kandethody M. Ramachandran
Publisher: Elsevier

Download and read online Mathematical Statistics with Applications in R in PDF and EPUB 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

Filename: mathematical-statistics-with-applications.pdf
ISBN: 9781111798789
Release Date: 2014-10-27
Number of pages: 944
Author: Dennis Wackerly
Publisher: Cengage Learning

Download and read online Mathematical Statistics with Applications in PDF and EPUB In their bestselling MATHEMATICAL STATISTICS WITH APPLICATIONS, premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps students discover the nature of statistics and understand its essential role in scientific research. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Filename: classic-topics-on-the-history-of-modern-mathematical-statistics.pdf
ISBN: 9781119127925
Release Date: 2016-04-04
Number of pages: 754
Author: Prakash Gorroochurn
Publisher: John Wiley & Sons

Download and read online Classic Topics on the History of Modern Mathematical Statistics in PDF and EPUB “There is nothing like it on the market...no others are as encyclopedic...the writing is exemplary: simple, direct, and competent.” — George 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 deals with 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.

Filename: modern-math-matical-statistics.pdf
ISBN: 0471814725
Release Date: 1988
Number of pages: 838
Author: Edward J. Dudewicz
Publisher: John Wiley & Sons Inc

Download and read online Modern math matical statistics in PDF and EPUB This modern treatment of mathematical statistics is concise, yet detailed enough to give readers a solid foundation in all aspects of the field. Treatment of each topic is thorough enough to make the coverage self-contained for a course in probability, and exceptional care has been taken to balance theory with applications. In addition to classical probability theory, such modern topics as order statistics and limiting distributions are discussed, along with applied examples from a wide variety of fields. Discussions include the core mathematical statistics topics of estimation, testing, and confidence intervals; ranking and selection procedures; decision theory; nonparametric statistics; regression and ANOVA; and robust statistical procedures. Computer-assisted data analysis is discussed at several points, reflecting the importance of statistical computation to the field. FORTRAN programs and BMDP routines are included, as well as the highly popular SAS routines. Also looks at the potential contribution of expert systems to statistics.

Filename: a-modern-introduction-to-probability-and-statistics.pdf
ISBN: 9781846281686
Release Date: 2006-03-30
Number of pages: 488
Author: F.M. Dekking
Publisher: Springer Science & Business Media

Download and read online A Modern Introduction to Probability and Statistics in PDF and EPUB Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Filename: student-solutions-manual-mathematical-statistics-with-applications.pdf
ISBN: 9780080964430
Release Date: 2010-05-22
Number of pages: 148
Author: K.M. Ramachandran
Publisher: Academic Press

Download and read online Student Solutions Manual Mathematical Statistics with Applications in PDF and EPUB 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

Filename: mathematical-statistics-with-resampling-and-r.pdf
ISBN: 9781118518953
Release Date: 2012-09-05
Number of pages: 432
Author: Laura M. Chihara
Publisher: John Wiley & Sons

Download and read online Mathematical Statistics with Resampling and R in PDF and EPUB This book bridges the latest software applications with the benefits of modern resampling techniques Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. This groundbreaking book shows how to apply modern resampling techniques to mathematical statistics. Extensively class-tested to ensure an accessible presentation, Mathematical Statistics with Resampling and R utilizes the powerful and flexible computer language R to underscore the significance and benefits of modern resampling techniques. The book begins by introducing permutation tests and bootstrap methods, motivating classical inference methods. Striking a balance between theory, computing, and applications, the authors explore additional topics such as: Exploratory data analysis Calculation of sampling distributions The Central Limit Theorem Monte Carlo sampling Maximum likelihood estimation and properties of estimators Confidence intervals and hypothesis tests Regression Bayesian methods Throughout the book, case studies on diverse subjects such as flight delays, birth weights of babies, and telephone company repair times illustrate the relevance of the real-world applications of the discussed material. Key definitions and theorems of important probability distributions are collected at the end of the book, and a related website is also available, featuring additional material including data sets, R scripts, and helpful teaching hints. Mathematical Statistics with Resampling and R is an excellent book for courses on mathematical statistics at the upper-undergraduate and graduate levels. It also serves as a valuable reference for applied statisticians working in the areas of business, economics, biostatistics, and public health who utilize resampling methods in their everyday work.

Filename: john-e-freund-s-mathematical-statistics-with-applications.pdf
ISBN: 032180709X
Release Date: 2014
Number of pages: 529
Author: Irwin Miller
Publisher: Pearson College Division

Download and read online John E Freund s Mathematical Statistics with Applications in PDF and EPUB John E. Freund's Mathematical Statistics with Applications , Eighth Edition, provides a calculus-based introduction to the theory and application of statistics, based on comprehensive coverage that reflects the latest in statistical thinking, the teaching of statistics, and current practices.

Filename: modern-concepts-and-theorems-of-mathematical-statistics.pdf
ISBN: 9781461248569
Release Date: 2012-12-06
Number of pages: 156
Author: Edward B. Manoukian
Publisher: Springer Science & Business Media

Download and read online Modern Concepts and Theorems of Mathematical Statistics in PDF and EPUB 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.

Filename: an-introduction-to-statistical-learning.pdf
ISBN: 9781461471387
Release Date: 2013-06-24
Number of pages: 426
Author: Gareth James
Publisher: Springer Science & Business Media

Download and read online An Introduction to Statistical Learning in PDF and EPUB An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Filename: basics-of-modern-mathematical-statistics.pdf
ISBN: 9783642399091
Release Date: 2014-10-25
Number of pages: 296
Author: Vladimir Spokoiny
Publisher: Springer

Download and read online Basics of Modern Mathematical Statistics in PDF and EPUB 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.