Mathematical Statistics with Applications in R

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

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  • Author : Kandethody M. Ramachandran
  • Publisher : Elsevier
  • Pages : 826 pages
  • ISBN : 012417132X
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKMathematical Statistics with Applications in R

Mathematical Statistics with Applications in R

Mathematical Statistics with Applications in R
  • Author : Kandethody M. Ramachandran,Chris P. Tsokos
  • Publisher : Elsevier
  • Release : 14 September 2014
GET THIS BOOKMathematical Statistics with Applications in R

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

Mathematical Statistics with Applications

Mathematical Statistics with Applications
  • Author : Dennis Wackerly,William Mendenhall,Richard L. Scheaffer
  • Publisher : Cengage Learning
  • Release : 27 October 2014
GET THIS BOOKMathematical Statistics with Applications

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

Modern Mathematical Statistics with Applications

Modern Mathematical Statistics with Applications
  • Author : Jay L. Devore,Kenneth N. Berk,Matthew A. Carlton
  • Publisher : Springer Nature
  • Release : 29 April 2021
GET THIS BOOKModern Mathematical Statistics with Applications

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

Mathematical Statistics With Applications

Mathematical Statistics With Applications
  • Author : Asha Seth Kapadia,Wenyaw Chan,Lemuel A. Moyé
  • Publisher : CRC Press
  • Release : 12 July 2017
GET THIS BOOKMathematical Statistics With Applications

Mathematical statistics typically represents one of the most difficult challenges in statistics, particularly for those with more applied, rather than mathematical, interests and backgrounds. Most textbooks on the subject provide little or no review of the advanced calculus topics upon which much of mathematical statistics relies and furthermore contain material that is wholly theoretical, thus presenting even greater challenges to those interested in applying advanced statistics to a specific area. Mathematical Statistics with Applications presents the background concepts and builds

Probability Theory with Applications

Probability Theory with Applications
  • Author : Malempati M. Rao,Randall J. Swift
  • Publisher : Springer Science & Business Media
  • Release : 15 March 2006
GET THIS BOOKProbability Theory with Applications

This is a revised and expanded edition of a successful graduate and reference text. The book is designed for a standard graduate course on probability theory, including some important applications. The new edition offers a detailed treatment of the core area of probability, and both structural and limit results are presented in detail. Compared to the first edition, the material and presentation are better highlighted; each chapter is improved and updated.

Mathematical Statistics with Applications

Mathematical Statistics with Applications
  • Author : Dennis Wackerly,William Mendenhall,Richard L. Scheaffer
  • Publisher : Duxbury Press
  • Release : 01 September 2007
GET THIS BOOKMathematical Statistics with Applications

Prepare for exams and succeed in your mathematics course with this comprehensive solutions manual! Featuring worked out-solutions to the problems in MATHEMATICAL STATISTICS WITH APPLICATIONS, 7th Edition, this manual shows you how to approach and solve problems using the same step-by-step explanations found in your textbook examples.

Probability and Statistics with Applications: A Problem Solving Text

Probability and Statistics with Applications: A Problem Solving Text
  • Author : Leonard Asimow, Ph.D., ASA,Mark Maxwell, Ph.D., ASA
  • Publisher : ACTEX Publications
  • Release : 30 June 2015
GET THIS BOOKProbability and Statistics with Applications: A Problem Solving Text

This text is listed on the Course of Reading for SOA Exam P. Probability and Statistics with Applications is an introductory textbook designed to make the subject accessible to college freshmen and sophomores concurrent with Calc II and III, with a prerequisite of just one smester of calculus. It is organized specifically to meet the needs of students who are preparing for the Society of Actuaries qualifying Examination P and Casualty Actuarial Society's new Exam S. Sample actuarial exam problems

Mathematical Statistics with Resampling and R

Mathematical Statistics with Resampling and R
  • Author : Laura M. Chihara,Tim C. Hesterberg
  • Publisher : John Wiley & Sons
  • Release : 17 September 2018
GET THIS BOOKMathematical Statistics with Resampling and R

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.

Mathematical Statistics

Mathematical Statistics
  • Author : Dieter Rasch,Dieter Schott
  • Publisher : John Wiley & Sons
  • Release : 09 January 2018
GET THIS BOOKMathematical Statistics

Explores mathematical statistics in its entirety—from the fundamentals to modern methods This book introduces readers to point estimation, confidence intervals, and statistical tests. Based on the general theory of linear models, it provides an in-depth overview of the following: analysis of variance (ANOVA) for models with fixed, random, and mixed effects; regression analysis is also first presented for linear models with fixed, random, and mixed effects before being expanded to nonlinear models; statistical multi-decision problems like statistical selection procedures (

Probability and Mathematical Statistics: Theory, Applications, and Practice in R

Probability and Mathematical Statistics: Theory, Applications, and Practice in R
  • Author : Mary C. Meyer
  • Publisher : SIAM
  • Release : 24 June 2019
GET THIS BOOKProbability and Mathematical Statistics: Theory, Applications, and Practice in R

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

Mathematical Statistics

Mathematical Statistics
  • Author : Jun Shao
  • Publisher : Springer Science & Business Media
  • Release : 03 February 2008
GET THIS BOOKMathematical Statistics

This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics. This new edition has been revised and updated and in this fourth printing, errors have been ironed out. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are useful in statistics. The second chapter introduces some fundamental concepts in statistical decision theory and inference. Subsequent chapters contain detailed studies on some

Mathematical Statistics

Mathematical Statistics
  • Author : Keith Knight
  • Publisher : CRC Press
  • Release : 24 November 1999
GET THIS BOOKMathematical Statistics

Traditional texts in mathematical statistics can seem - to some readers-heavily weighted with optimality theory of the various flavors developed in the 1940s and50s, and not particularly relevant to statistical practice. Mathematical Statistics stands apart from these treatments. While mathematically rigorous, its focus is on providing a set of useful tools that allow students to understand the theoretical underpinnings of statistical methodology. The author concentrates on inferential procedures within the framework of parametric models, but - acknowledging that models