Probability And Mathematical Statistics Theory Applications And Practice In R

Author : Mary C. Meyer
Publisher : SIAM
Page : 707 pages
File Size : 48,6 Mb
Release : 2019-06-24
Category : Mathematics
ISBN : 9781611975789

Get Book

Probability and Mathematical Statistics: Theory, Applications, and Practice in R by Mary C. Meyer Pdf

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.

Author : Kandethody M. Ramachandran,Chris P. Tsokos
Publisher : Academic Press
Page : 703 pages
File Size : 54,7 Mb
Release : 2020-05-14
Category : Mathematics
ISBN : 9780128178164

Get Book

Mathematical Statistics with Applications in R by Kandethody M. Ramachandran,Chris P. Tsokos Pdf

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

Author : Dieter Rasch,Rob Verdooren,Jürgen Pilz
Publisher : John Wiley & Sons
Page : 509 pages
File Size : 48,9 Mb
Release : 2019-10-07
Category : Mathematics
ISBN : 9781119551522

Get Book

Applied Statistics by Dieter Rasch,Rob Verdooren,Jürgen Pilz Pdf

Instructs readers on how to use methods of statistics and experimental design with R software Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds from a strong theoretical background, but it is practically oriented to develop one's ability to tackle new and non-standard problems confidently. Taking a practical approach to applied statistics, this user-friendly guide teaches readers how to use methods of statistics and experimental design without going deep into the theory. Applied Statistics: Theory and Problem Solutions with R includes chapters that cover R package sampling procedures, analysis of variance, point estimation, and more. It follows on the heels of Rasch and Schott's Mathematical Statistics via that book's theoretical background—taking the lessons learned from there to another level with this book’s addition of instructions on how to employ the methods using R. But there are two important chapters not mentioned in the theoretical back ground as Generalised Linear Models and Spatial Statistics. Offers a practical over theoretical approach to the subject of applied statistics Provides a pre-experimental as well as post-experimental approach to applied statistics Features classroom tested material Applicable to a wide range of people working in experimental design and all empirical sciences Includes 300 different procedures with R and examples with R-programs for the analysis and for determining minimal experimental sizes Applied Statistics: Theory and Problem Solutions with R will appeal to experimenters, statisticians, mathematicians, and all scientists using statistical procedures in the natural sciences, medicine, and psychology amongst others.

Author : Randall Pruim
Publisher : American Mathematical Soc.
Page : 820 pages
File Size : 44,7 Mb
Release : 2018-04-04
Category : Mathematical statistics
ISBN : 9781470428488

Get Book

Foundations and Applications of Statistics by Randall Pruim Pdf

Foundations and Applications of Statistics simultaneously emphasizes both the foundational and the computational aspects of modern statistics. Engaging and accessible, this book is useful to undergraduate students with a wide range of backgrounds and career goals. The exposition immediately begins with statistics, presenting concepts and results from probability along the way. Hypothesis testing is introduced very early, and the motivation for several probability distributions comes from p-value computations. Pruim develops the students' practical statistical reasoning through explicit examples and through numerical and graphical summaries of data that allow intuitive inferences before introducing the formal machinery. The topics have been selected to reflect the current practice in statistics, where computation is an indispensible tool. In this vein, the statistical computing environment R is used throughout the text and is integral to the exposition. Attention is paid to developing students' mathematical and computational skills as well as their statistical reasoning. Linear models, such as regression and ANOVA, are treated with explicit reference to the underlying linear algebra, which is motivated geometrically. Foundations and Applications of Statistics discusses both the mathematical theory underlying statistics and practical applications that make it a powerful tool across disciplines. The book contains ample material for a two-semester course in undergraduate probability and statistics. A one-semester course based on the book will cover hypothesis testing and confidence intervals for the most common situations. In the second edition, the R code has been updated throughout to take advantage of new R packages and to illustrate better coding style. New sections have been added covering bootstrap methods, multinomial and multivariate normal distributions, the delta method, numerical methods for Bayesian inference, and nonlinear least squares. Also, the use of matrix algebra has been expanded, but remains optional, providing instructors with more options regarding the amount of linear algebra required.

Author : Anonim
Publisher : Unknown
Page : 456 pages
File Size : 41,9 Mb
Release : 1988
Category : Mathematical statistics
ISBN : OCLC:18748496

Get Book

Probability Theory and Mathematical Statistics with Applications by Anonim Pdf

Author : Laura M. Chihara,Tim C. Hesterberg
Publisher : John Wiley & Sons
Page : 560 pages
File Size : 40,8 Mb
Release : 2018-09-19
Category : Mathematics
ISBN : 9781119416548

Get Book

Mathematical Statistics with Resampling and R by Laura M. Chihara,Tim C. Hesterberg Pdf

This thoroughly updated second edition combines 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. The second edition of Mathematical Statistics with Resampling and R combines modern resampling techniques and mathematical statistics. This book has been classroom-tested to ensure an accessible presentation, uses the powerful and flexible computer language R for data analysis and explores the benefits of modern resampling techniques. This book offers an introduction to permutation tests and bootstrap methods that can serve to motivate classical inference methods. The book strikes a balance between theory, computing, and applications, and the new edition explores additional topics including consulting, paired t test, ANOVA and Google Interview Questions. Throughout the book, new and updated case studies are included representing a diverse range of subjects such as flight delays, birth weights of babies, and telephone company repair times. These illustrate the relevance of the real-world applications of the material. This new edition: • Puts the focus on statistical consulting that emphasizes giving a client an understanding of data and goes beyond typical expectations • Presents new material on topics such as the paired t test, Fisher's Exact Test and the EM algorithm • Offers a new section on "Google Interview Questions" that illustrates statistical thinking • Provides a new chapter on ANOVA • Contains more exercises and updated case studies, data sets, and R code Written for undergraduate students in a mathematical statistics course as well as practitioners and researchers, the second edition of Mathematical Statistics with Resampling and R presents a revised and updated guide for applying the most current resampling techniques to mathematical statistics.

Author : Amy S. Wagaman,Robert P. Dobrow
Publisher : John Wiley & Sons
Page : 546 pages
File Size : 46,6 Mb
Release : 2021-06-11
Category : Mathematics
ISBN : 9781119692416

Get Book

Probability by Amy S. Wagaman,Robert P. Dobrow Pdf

Discover the latest edition of a practical introduction to the theory of probability, complete with R code samples In the newly revised Second Edition of Probability: With Applications and R, distinguished researchers Drs. Robert Dobrow and Amy Wagaman deliver a thorough introduction to the foundations of probability theory. The book includes a host of chapter exercises, examples in R with included code, and well-explained solutions. With new and improved discussions on reproducibility for random numbers and how to set seeds in R, and organizational changes, the new edition will be of use to anyone taking their first probability course within a mathematics, statistics, engineering, or data science program. New exercises and supplemental materials support more engagement with R, and include new code samples to accompany examples in a variety of chapters and sections that didn’t include them in the first edition. The new edition also includes for the first time: A thorough discussion of reproducibility in the context of generating random numbers Revised sections and exercises on conditioning, and a renewed description of specifying PMFs and PDFs Substantial organizational changes to improve the flow of the material Additional descriptions and supplemental examples to the bivariate sections to assist students with a limited understanding of calculus Perfect for upper-level undergraduate students in a first course on probability theory, Probability: With Applications and R is also ideal for researchers seeking to learn probability from the ground up or those self-studying probability for the purpose of taking advanced coursework or preparing for actuarial exams.

Author : Robert P. Dobrow
Publisher : John Wiley & Sons
Page : 366 pages
File Size : 55,9 Mb
Release : 2013-10-16
Category : Mathematics
ISBN : 9781118589441

Get Book

Probability by Robert P. Dobrow Pdf

An introduction to probability at the undergraduate level Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability. With real-life examples and thoughtful exercises from fields as diverse as biology, computer science, cryptology, ecology, public health, and sports, the book is accessible for a variety of readers. The book’s emphasis on simulation through the use of the popular R software language clarifies and illustrates key computational and theoretical results. Probability: With Applications and R helps readers develop problem-solving skills and delivers an appropriate mix of theory and application. The book includes: Chapters covering first principles, conditional probability, independent trials, random variables, discrete distributions, continuous probability, continuous distributions, conditional distribution, and limits An early introduction to random variables and Monte Carlo simulation and an emphasis on conditional probability, conditioning, and developing probabilistic intuition An R tutorial with example script files Many classic and historical problems of probability as well as nontraditional material, such as Benford’s law, power-law distributions, and Bayesian statistics A topics section with suitable material for projects and explorations, such as random walk on graphs, Markov chains, and Markov chain Monte Carlo Chapter-by-chapter summaries and hundreds of practical exercises Probability: With Applications and R is an ideal text for a beginning course in probability at the undergraduate level.

Author : Kandethody M. Ramachandran,Chris P. Tsokos
Publisher : Elsevier
Page : 826 pages
File Size : 55,9 Mb
Release : 2014-09-14
Category : Mathematics
ISBN : 9780124171329

Get Book

Mathematical Statistics with Applications in R by Kandethody M. Ramachandran,Chris P. Tsokos Pdf

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

Author : Laura M. Chihara,Tim C. Hesterberg,Robert P. Dobrow
Publisher : Wiley
Page : 0 pages
File Size : 43,7 Mb
Release : 2014-03-31
Category : Mathematics
ISBN : 1118947436

Get Book

Mathematical Statistics with Resampling and R & Probability with Applications and R Set by Laura M. Chihara,Tim C. Hesterberg,Robert P. Dobrow Pdf

An essential resource to simulations to support an understanding of statistics Mathematical Statistics with Resampling and R & Probability with Applications and R Set offers a resource for intermediate and advanced statistics students who want to achieve an in-depth understanding of resampling techniques backed by practical implementation. This text is recommended for anyone with a background in mathematics, probability, and basic statistics who wants to learn about the theory and about resampling and how it relates to traditional methods, and how to implement resampling in R.

Author : Prabhanjan N. Tattar,Suresh Ramaiah,B. G. Manjunath
Publisher : John Wiley & Sons
Page : 696 pages
File Size : 48,8 Mb
Release : 2016-03-15
Category : Computers
ISBN : 9781119152736

Get Book

A Course in Statistics with R by Prabhanjan N. Tattar,Suresh Ramaiah,B. G. Manjunath Pdf

Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R basics and quickly covers visualization and exploratory analysis. Probability and statistical inference, inclusive of classical, nonparametric, and Bayesian schools, is developed with definitions, motivations, mathematical expression and R programs in a way which will help the reader to understand the mathematical development as well as R implementation. Linear regression models, experimental designs, multivariate analysis, and categorical data analysis are treated in a way which makes effective use of visualization techniques and the related statistical techniques underlying them through practical applications, and hence helps the reader to achieve a clear understanding of the associated statistical models. Key features: Integrates R basics with statistical concepts Provides graphical presentations inclusive of mathematical expressions Aids understanding of limit theorems of probability with and without the simulation approach Presents detailed algorithmic development of statistical models from scratch Includes practical applications with over 50 data sets

Author : Maria Dolores Ugarte,Ana F. Militino,Alan T. Arnholt
Publisher : CRC Press
Page : 710 pages
File Size : 49,5 Mb
Release : 2008-04-11
Category : Mathematics
ISBN : 9781584888925

Get Book

Probability and Statistics with R by Maria Dolores Ugarte,Ana F. Militino,Alan T. Arnholt Pdf

Designed for an intermediate undergraduate course, Probability and Statistics with R shows students how to solve various statistical problems using both parametric and nonparametric techniques via the open source software R. It provides numerous real-world examples, carefully explained proofs, end-of-chapter problems, and illuminating graphs

Author : Sujit K. Sahu
Publisher : Springer Nature
Page : 559 pages
File Size : 51,8 Mb
Release : 2024-06-15
Category : Electronic
ISBN : 9783031378652

Get Book

Introduction to Probability, Statistics & R by Sujit K. Sahu Pdf

Author : Katarzyna Stapor
Publisher : Springer Nature
Page : 163 pages
File Size : 42,8 Mb
Release : 2020-05-22
Category : Mathematics
ISBN : 9783030457990

Get Book

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 : G. Jay Kerns
Publisher : Lulu.com
Page : 388 pages
File Size : 43,6 Mb
Release : 2010-01-10
Category : Education
ISBN : 9780557249794

Get Book

Introduction to Probability and Statistics Using R by G. Jay Kerns Pdf

This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.