Mathematical Statistics with Applications in R

• Author : Kandethody M. Ramachandran,Chris P. Tsokos
• Publisher : Academic Press
• Release : 14 May 2020

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

• Author : Kandethody M. Ramachandran,Chris P. Tsokos
• Publisher : Elsevier
• Release : 14 September 2014

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

• Author : K. M. Ramachandran,Chris P. Tsokos
• Publisher : Academic Press
• Release : 18 August 2014

Mathematical Statistics with Applications, Second Edition, gives an up-to-date introduction to the theory of statistics with a wealth of real-world applications that will help students approach statistical problem solving in a logical manner. The book introduces 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. Goodness of fit

• Author : Dennis D. Wackerly,William Mendenhall,Richard L. Scheaffer
• Publisher : Duxbury Press
• Release : 01 August 2021

This is the most widely used mathematical statistics text at the top 200 universities in the United States. Premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid undergraduate 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.

• Author : Jay L. Devore,Kenneth N. Berk
• Publisher : Springer Science & Business Media
• Release : 06 December 2011

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

• Author : Laura M. Chihara,Tim C. Hesterberg
• Publisher : John Wiley & Sons
• Release : 19 September 2018

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.

• Author : Dennis D. Wackerly,William Mendenhall,Richard L. Scheaffer
• Publisher : Cengage Learning
• Release : 01 August 2021

The authors present the theory of statistics in the context of practical problem solving and real world applications. This practical approach helps you discover the nature of statistics and comprehend its essential role in scientific research.--

• Author : Mary C. Meyer
• Publisher : SIAM
• Release : 24 June 2019

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

• Author : Kandethody M. Ramachandran,Chris P. Tsokos
• Publisher : Academic Press
• Release : 13 March 2009

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

• Author : Laura M. Chihara,Tim C. Hesterberg
• Publisher : John Wiley & Sons
• Release : 06 September 2011

The Central Limit Theorem.

• Author : William Mendenhall,Richard L. Scheaffer,Dennis D. Wackerly
• Publisher : Arden Shakespeare
• Release : 01 August 1986

This is the most widely used mathematical statistics text at the top 200 universities in the United States. Premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid undergraduate 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.

• Author : Richard J. Larsen,Morris L. Marx
• Publisher : Pearson
• Release : 05 January 2017

For courses in Mathematical Statistics Introducing the principles of statistics and data modeling Written by famous statistician John Tukey, Introduction to Mathematical Statistics and Its Applications , 6th Edition is a high-level calculus student's first exposure to mathematical statistics. This book provides students who have already taken three or more semesters of calculus with the background to apply statistical principles. Meaty enough to guide a two-semester course, the book touches on both statistics and experimental design, which teaches students various ways

• Author : Joachim Kunert,Götz Trenkler
• Publisher : Unknown
• Release : 01 August 2021

• Author : Dennis Wackerly,William Mendenhall,Richard L. Scheaffer
• Publisher : Cengage Learning
• Release : 27 October 2014

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

• Author : Laura M. Chihara,Tim C. Hesterberg,Robert P. Dobrow
• Publisher : Wiley
• Release : 31 March 2014

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, M"athematical 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