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 : 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 : 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 : 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 : Dennis D. Wackerly,William Mendenhall,Richard L. Scheaffer
• Publisher : Duxbury Press
• Release : 27 January 2023

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 : Marc Moore,Constance van Eeden
• Publisher : IMS
• Release : 27 January 2023

• Author : Asha Seth Kapadia,Wenyaw Chan,Lemuel A. Moyé
• Publisher : CRC Press
• Release : 12 July 2017

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

• 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 : 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 : William M. Mendenhall,Terry L. Sincich
• Publisher : CRC Press
• Release : 05 April 2016

Prepare Your Students for Statistical Work in the Real WorldStatistics for Engineering and the Sciences, Sixth Edition is designed for a two-semester introductory course on statistics for students majoring in engineering or any of the physical sciences. This popular text continues to teach students the basic concepts of data description and statist

• Author : Jonathan D. Cryer,Kung-Sik Chan
• Publisher : Springer Science & Business Media
• Release : 06 March 2008

This book has been developed for a one-semester course usually attended by students in statistics, economics, business, engineering, and quantitative social sciences. A unique feature of this edition is its integration with the R computing environment. Basic applied statistics is assumed through multiple regression. Calculus is assumed only to the extent of minimizing sums of squares but a calculus-based introduction to statistics is necessary for a thorough understanding of some of the theory. Actual time series data drawn from various

• Author : Laura M. Chihara,Tim C. Hesterberg
• Publisher : John Wiley & Sons
• Release : 17 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 : Wilfried Grossmann,G. Pflug,Wolfgang Wertz
• Publisher : Springer
• Release : 27 January 1985

Proceedings of the 4th Pannonian Symposium on Mathematical Statistics, Bad Tatzmannsdorf, Austria, 4-10 September 1983, Volume B.

• Author : Wolfgang Karl Härdle,Vladimir Spokoiny,Vladimir Panov,Weining Wang
• Publisher : Springer
• Release : 20 November 2013

​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

• Author : Anonim
• Publisher : Walter de Gruyter GmbH & Co KG
• Release : 26 May 2020