Mathematical Statistics With Applications In R

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Mathematical Statistics With Applications

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Author : Kandethody M. Ramachandran
language : en
Publisher: Academic Press
Release Date : 2009-03-13

Mathematical Statistics With Applications written by Kandethody M. Ramachandran and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-03-13 with Mathematics categories.

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

Mathematical Statistics With Applications In R

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Author : Kandethody M. Ramachandran
language : en
Publisher: Academic Press
Release Date : 2020-05-14

Mathematical Statistics With Applications In R written by Kandethody M. Ramachandran and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-14 with Mathematics categories.

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

Mathematical Statistics With Applications In R

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Author : Kandethody M. Ramachandran
language : en
Publisher: Elsevier
Release Date : 2014-09-14

Mathematical Statistics With Applications In R written by Kandethody M. Ramachandran and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-14 with Mathematics categories.

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

Mathematical Statistics With Resampling And R

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Author : Laura M. Chihara
language : en
Publisher: John Wiley & Sons
Release Date : 2022-08-09

Mathematical Statistics With Resampling And R written by Laura M. Chihara and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-09 with Mathematics categories.

Mathematical Statistics with Resampling and R This thoroughly updated third 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 third edition of Mathematical Statistics with Resampling and R combines modern resampling techniques and mathematical statistics. This book is classroom-tested to ensure an accessible presentation, and uses the powerful and flexible computer language R for data analysis. This book introduces permutation tests and bootstrap methods to motivate classical inference methods, as well as to be utilized as useful tools in their own right when classical methods are inaccurate or unavailable. The book strikes a balance between simulation, computing, theory, data, and applications. Throughout the book, new and updated case studies representing a diverse range of subjects, such as flight delays, birth weights of babies, U.S. demographics, views on sociological issues, and problems at Google and Instacart, illustrate the relevance of mathematical statistics to real-world applications. Changes and additions to the third edition include: New and updated case studies that incorporate contemporary subjects like COVID-19 Several new sections, including introductory material on causal models and regression methods for causal modeling in practice Modern terminology distinguishing statistical discernibility and practical importance New exercises and examples, data sets, and R code, using dplyr and ggplot2 A complete instructor’s solutions manual A new github site that contains code, data sets, additional topics, and instructor resources Mathematical Statistics with Resampling and R is an ideal textbook for undergraduate and graduate students in mathematical statistics courses, as well as practitioners and researchers looking to expand their toolkit of resampling and classical techniques.

Mathematical Statistics With Applications

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Author : K. M. Ramachandran
language : en
Publisher:
Release Date : 2009

Mathematical Statistics With Applications written by K. M. Ramachandran and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.

Modern Mathematical Statistics With Applications

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Author : Jay L. Devore
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-12-07

Modern Mathematical Statistics With Applications written by Jay L. Devore and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-07 with Mathematics categories.

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.

Mathematical Statistics And Applications

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Author : Wilfried Grossmann
language : en
Publisher: Springer
Release Date : 1985

Mathematical Statistics And Applications written by Wilfried Grossmann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Mathematics categories.

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

Nuclear Science Abstracts

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Author :
language : en
Publisher:
Release Date : 1956

Nuclear Science Abstracts written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1956 with Nuclear energy categories.

A Course In Mathematical Statistics And Large Sample Theory

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Author : Rabi Bhattacharya
language : en
Publisher: Springer
Release Date : 2016-08-13

A Course In Mathematical Statistics And Large Sample Theory written by Rabi Bhattacharya and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-13 with Mathematics categories.

This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability. It provides a rigorous presentation of the core of mathematical statistics. Part I of this book constitutes a one-semester course on basic parametric mathematical statistics. Part II deals with the large sample theory of statistics - parametric and nonparametric, and its contents may be covered in one semester as well. Part III provides brief accounts of a number of topics of current interest for practitioners and other disciplines whose work involves statistical methods.

Statistics For Engineering And The Sciences

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Author : William M. Mendenhall
language : en
Publisher: CRC Press
Release Date : 2016-04-05

Statistics For Engineering And The Sciences written by William M. Mendenhall and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-05 with Mathematics categories.

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