Probability and Mathematical Statistics: Theory, Applications, and Practice in R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Probability and Mathematical Statistics: Theory, Applications, and Practice in R write by Mary C. Meyer. This book was released on 2019-06-24. Probability and Mathematical Statistics: Theory, Applications, and Practice in R available in PDF, EPUB and Kindle. 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.
Mathematical Statistics with Applications in R
Mathematical Statistics with Applications in R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Mathematical Statistics with Applications in R write by Kandethody M. Ramachandran. This book was released on 2020-05-14. Mathematical Statistics with Applications in R available in PDF, EPUB and Kindle. 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
Applied Statistics
Applied Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applied Statistics write by Dieter Rasch. This book was released on 2019-10-07. Applied Statistics available in PDF, EPUB and Kindle. Instructs readers on how to use methods of statistics and experimental design with R software Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds from a strong theoretical background, but it is practically oriented to develop one's ability to tackle new and non-standard problems confidently. Taking a practical approach to applied statistics, this user-friendly guide teaches readers how to use methods of statistics and experimental design without going deep into the theory. Applied Statistics: Theory and Problem Solutions with R includes chapters that cover R package sampling procedures, analysis of variance, point estimation, and more. It follows on the heels of Rasch and Schott's Mathematical Statistics via that book's theoretical background—taking the lessons learned from there to another level with this book’s addition of instructions on how to employ the methods using R. But there are two important chapters not mentioned in the theoretical back ground as Generalised Linear Models and Spatial Statistics. Offers a practical over theoretical approach to the subject of applied statistics Provides a pre-experimental as well as post-experimental approach to applied statistics Features classroom tested material Applicable to a wide range of people working in experimental design and all empirical sciences Includes 300 different procedures with R and examples with R-programs for the analysis and for determining minimal experimental sizes Applied Statistics: Theory and Problem Solutions with R will appeal to experimenters, statisticians, mathematicians, and all scientists using statistical procedures in the natural sciences, medicine, and psychology amongst others.
Probability
Probability - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Probability write by Amy S. Wagaman. This book was released on 2021-06-11. Probability available in PDF, EPUB and Kindle. Discover the latest edition of a practical introduction to the theory of probability, complete with R code samples In the newly revised Second Edition of Probability: With Applications and R, distinguished researchers Drs. Robert Dobrow and Amy Wagaman deliver a thorough introduction to the foundations of probability theory. The book includes a host of chapter exercises, examples in R with included code, and well-explained solutions. With new and improved discussions on reproducibility for random numbers and how to set seeds in R, and organizational changes, the new edition will be of use to anyone taking their first probability course within a mathematics, statistics, engineering, or data science program. New exercises and supplemental materials support more engagement with R, and include new code samples to accompany examples in a variety of chapters and sections that didn’t include them in the first edition. The new edition also includes for the first time: A thorough discussion of reproducibility in the context of generating random numbers Revised sections and exercises on conditioning, and a renewed description of specifying PMFs and PDFs Substantial organizational changes to improve the flow of the material Additional descriptions and supplemental examples to the bivariate sections to assist students with a limited understanding of calculus Perfect for upper-level undergraduate students in a first course on probability theory, Probability: With Applications and R is also ideal for researchers seeking to learn probability from the ground up or those self-studying probability for the purpose of taking advanced coursework or preparing for actuarial exams.
Probability
Probability - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Probability write by Robert P. Dobrow. This book was released on 2013-10-16. Probability available in PDF, EPUB and Kindle. An introduction to probability at the undergraduate level Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability. With real-life examples and thoughtful exercises from fields as diverse as biology, computer science, cryptology, ecology, public health, and sports, the book is accessible for a variety of readers. The book’s emphasis on simulation through the use of the popular R software language clarifies and illustrates key computational and theoretical results. Probability: With Applications and R helps readers develop problem-solving skills and delivers an appropriate mix of theory and application. The book includes: Chapters covering first principles, conditional probability, independent trials, random variables, discrete distributions, continuous probability, continuous distributions, conditional distribution, and limits An early introduction to random variables and Monte Carlo simulation and an emphasis on conditional probability, conditioning, and developing probabilistic intuition An R tutorial with example script files Many classic and historical problems of probability as well as nontraditional material, such as Benford’s law, power-law distributions, and Bayesian statistics A topics section with suitable material for projects and explorations, such as random walk on graphs, Markov chains, and Markov chain Monte Carlo Chapter-by-chapter summaries and hundreds of practical exercises Probability: With Applications and R is an ideal text for a beginning course in probability at the undergraduate level.
