Mathematical Statistics with Applications in R

Mathematical Statistics with Applications in R PDF

Author: Kandethody M. Ramachandran

Publisher: Elsevier

Published: 2014-09-14

Total Pages: 825

ISBN-13: 012417132X

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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 Applications

Mathematical Statistics with Applications PDF

Author: Dennis Wackerly

Publisher: Cengage Learning

Published: 2014-10-27

Total Pages: 944

ISBN-13: 9780495110811

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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 be available in the ebook version.

Essentials of Mathematical Statistics

Essentials of Mathematical Statistics PDF

Author: Brian Albright

Publisher: Jones & Bartlett Publishers

Published: 2014

Total Pages: 607

ISBN-13: 144968534X

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This text combines the topics generally found in main-stream elementary statistics books with the essentials of the underlying theory. The book begins with an axiomatic treatment of probability followed by chapters on discrete and continuous random variables and their associated distributions. It then introduces basic statistical concepts including summarizing data and interval parameter estimation, stressing the connection between probability and statistics. Final chapters introduce hypothesis testing, regression, and non-parametric techniques. All chapters provide a balance between conceptual understanding and theoretical understanding of the topics at hand.

Mathematical Statistics and Data Analysis

Mathematical Statistics and Data Analysis PDF

Author: John A. Rice

Publisher:

Published: 2007

Total Pages: 603

ISBN-13: 9780495118688

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This is the first text in a generation to re-examine the purpose of the mathematical statistics course. The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts that are set in abstract settings.

John E. Freund's Mathematical Statistics with Applications

John E. Freund's Mathematical Statistics with Applications PDF

Author: Irwin Miller

Publisher: Pearson

Published: 2015-12-03

Total Pages: 549

ISBN-13: 0134291670

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This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. John E. Freund's Mathematical Statistics with Applications , Eighth Edition, provides a calculus-based introduction to the theory and application of statistics, based on comprehensive coverage that reflects the latest in statistical thinking, the teaching of statistics, and current practices.

Mathematical Statistics with Applications in R

Mathematical Statistics with Applications in R PDF

Author: Kandethody M. Ramachandran

Publisher: Academic Press

Published: 2020-05-14

Total Pages: 703

ISBN-13: 0128178167

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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

Mathematical Statistics with Applications PDF

Author: Kandethody M. Ramachandran

Publisher: Academic Press

Published: 2009-03-13

Total Pages: 849

ISBN-13: 0080951708

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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

Stochastic Modeling and Mathematical Statistics

Stochastic Modeling and Mathematical Statistics PDF

Author: Francisco J. Samaniego

Publisher: CRC Press

Published: 2014-01-14

Total Pages: 622

ISBN-13: 1466560479

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Provides a Solid Foundation for Statistical Modeling and Inference and Demonstrates Its Breadth of Applicability Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists addresses core issues in post-calculus probability and statistics in a way that is useful for statistics and mathematics majors as well

John E. Freund's Mathematical Statistics with Applications

John E. Freund's Mathematical Statistics with Applications PDF

Author: Irwin Miller

Publisher: Pearson Educacion

Published: 2012-12-07

Total Pages: 544

ISBN-13: 9780321904409

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John E. Freund's Mathematical Statistics with Applications, Eighth Edition, provides a calculus-based introduction to the theory and application of statistics, based on comprehensive coverage that reflects the latest in statistical thinking, the teaching of statistics, and current practices.