Mathematical Statistics with Applications in R PDF

Author: Kandethody M. Ramachandran
Publisher: Academic Press
Release: 2020-05-14
Size: 12.62 MB
Format: PDF
Category : Mathematics
Languages : en
Pages : 704
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Mathematical Statistics With Applications In R

Mathematical Statistics With Applications In R by Kandethody M. Ramachandran, Mathematical Statistics With Applications In R Books available in PDF, EPUB, Mobi Format. Download Mathematical Statistics With Applications In R books, 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 PDF

Author: Kandethody M. Ramachandran
Publisher: Elsevier
Release: 2014-09-14
Size: 76.32 MB
Format: PDF
Category : Mathematics
Languages : en
Pages : 826
View: 4898

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Mathematical Statistics With Applications In R

Mathematical Statistics With Applications In R by Kandethody M. Ramachandran, Mathematical Statistics With Applications In R Books available in PDF, EPUB, Mobi Format. Download Mathematical Statistics With Applications In R books, 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


Probability and Mathematical Statistics Theory Applications and Practice in R PDF

Author: Mary C. Meyer
Publisher: SIAM
Release: 2019-06-24
Size: 26.98 MB
Format: PDF, Kindle
Category : Mathematics
Languages : en
Pages : 707
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Probability And Mathematical Statistics Theory Applications And Practice In R

Mathematical Statistics With Applications In R by Mary C. Meyer, Probability And Mathematical Statistics Theory Applications And Practice In R Books available in PDF, EPUB, Mobi Format. Download Probability And Mathematical Statistics Theory Applications And Practice In R books, 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 examples utilizing R within the chapters are instructive and practical. Exercises that focus on real-world applications without sacrificing mathematical rigor are included, along with more than 200 figures that help clarify both concepts and applications. In addition, the book features two helpful appendices: annotated solutions to 700 exercises and a Review of Useful Math. Written for use in applied masters classes, Probability and Mathematical Statistics: Theory, Applications, and Practice in R is also suitable for advanced undergraduates and for self-study by applied mathematicians and statisticians and qualitatively inclined engineers and scientists.


Modern Mathematical Statistics with Applications PDF

Author: Jay L. Devore
Publisher: Springer Nature
Release:
Size: 37.52 MB
Format: PDF, Mobi
Category :
Languages : en
Pages :
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Modern Mathematical Statistics With Applications

Mathematical Statistics With Applications In R by Jay L. Devore, Modern Mathematical Statistics With Applications Books available in PDF, EPUB, Mobi Format. Download Modern Mathematical Statistics With Applications books,


Advanced Statistics with Applications in R PDF

Author: Eugene Demidenko
Publisher: John Wiley & Sons
Release: 2019-11-12
Size: 74.31 MB
Format: PDF, ePub, Docs
Category : Mathematics
Languages : en
Pages : 880
View: 6243

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Advanced Statistics With Applications In R

Mathematical Statistics With Applications In R by Eugene Demidenko, Advanced Statistics With Applications In R Books available in PDF, EPUB, Mobi Format. Download Advanced Statistics With Applications In R books, Advanced Statistics with Applications in R fills the gap between several excellent theoretical statistics textbooks and many applied statistics books where teaching reduces to using existing packages. This book looks at what is under the hood. Many statistics issues including the recent crisis with p-value are caused by misunderstanding of statistical concepts due to poor theoretical background of practitioners and applied statisticians. This book is the product of a forty-year experience in teaching of probability and statistics and their applications for solving real-life problems. There are more than 442 examples in the book: basically every probability or statistics concept is illustrated with an example accompanied with an R code. Many examples, such as Who said π? What team is better? The fall of the Roman empire, James Bond chase problem, Black Friday shopping, Free fall equation: Aristotle or Galilei, and many others are intriguing. These examples cover biostatistics, finance, physics and engineering, text and image analysis, epidemiology, spatial statistics, sociology, etc. Advanced Statistics with Applications in R teaches students to use theory for solving real-life problems through computations: there are about 500 R codes and 100 datasets. These data can be freely downloaded from the author's website dartmouth.edu/~eugened. This book is suitable as a text for senior undergraduate students with major in statistics or data science or graduate students. Many researchers who apply statistics on the regular basis find explanation of many fundamental concepts from the theoretical perspective illustrated by concrete real-world applications.


Mathematical Statistics with Applications PDF

Author: Dennis Wackerly
Publisher: Cengage Learning
Release: 2014-10-27
Size: 53.94 MB
Format: PDF, ePub, Docs
Category : Mathematics
Languages : en
Pages : 944
View: 2487

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Mathematical Statistics With Applications

Mathematical Statistics With Applications In R by Dennis Wackerly, Mathematical Statistics With Applications Books available in PDF, EPUB, Mobi Format. Download Mathematical Statistics With Applications books, 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.


An Introduction to Statistical Learning PDF

Author: Gareth James
Publisher: Springer Science & Business Media
Release: 2013-06-24
Size: 28.23 MB
Format: PDF, Mobi
Category : Mathematics
Languages : en
Pages : 426
View: 3023

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An Introduction To Statistical Learning

Mathematical Statistics With Applications In R by Gareth James, An Introduction To Statistical Learning Books available in PDF, EPUB, Mobi Format. Download An Introduction To Statistical Learning books, An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.


Modern Mathematical Statistics with Applications PDF

Author: Jay L. Devore
Publisher: Springer Science & Business Media
Release: 2011-12-06
Size: 77.55 MB
Format: PDF
Category : Mathematics
Languages : en
Pages : 845
View: 3589

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Modern Mathematical Statistics With Applications

Mathematical Statistics With Applications In R by Jay L. Devore, Modern Mathematical Statistics With Applications Books available in PDF, EPUB, Mobi Format. Download Modern Mathematical Statistics With Applications books, 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 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 with Resampling and R PDF

Author: Laura M. Chihara
Publisher: John Wiley & Sons
Release: 2018-09-17
Size: 52.60 MB
Format: PDF, Kindle
Category : Mathematics
Languages : en
Pages : 560
View: 4226

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Mathematical Statistics With Resampling And R

Mathematical Statistics With Applications In R by Laura M. Chihara, Mathematical Statistics With Resampling And R Books available in PDF, EPUB, Mobi Format. Download Mathematical Statistics With Resampling And R books, 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. This book offers an introduction to permutation tests and bootstrap methods that can serve to motivate classical inference methods. The book strikes a balance between theory, computing, and applications, and the new edition explores additional topics including consulting, paired t test, ANOVA and Google Interview Questions. Throughout the book, new and updated case studies are included representing a diverse range of subjects such as flight delays, birth weights of babies, and telephone company repair times. These illustrate the relevance of the real-world applications of the material. This new edition: • Puts the focus on statistical consulting that emphasizes giving a client an understanding of data and goes beyond typical expectations • Presents new material on topics such as the paired t test, Fisher's Exact Test and the EM algorithm • Offers a new section on "Google Interview Questions" that illustrates statistical thinking • Provides a new chapter on ANOVA • Contains more exercises and updated case studies, data sets, and R code Written for undergraduate students in a mathematical statistics course as well as practitioners and researchers, the second edition of Mathematical Statistics with Resampling and R presents a revised and updated guide for applying the most current resampling techniques to mathematical statistics.


Introductory Statistics with R PDF

Author: Peter Dalgaard
Publisher: Springer Science & Business Media
Release: 2008-06-27
Size: 35.89 MB
Format: PDF, Kindle
Category : Mathematics
Languages : en
Pages : 364
View: 7164

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Introductory Statistics With R

Mathematical Statistics With Applications In R by Peter Dalgaard, Introductory Statistics With R Books available in PDF, EPUB, Mobi Format. Download Introductory Statistics With R books, This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.