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Questions in Dataviz: A Design-Driven Process for Data Visualisation (AK Peters Visualization Series)
by Neil RichardsThis book takes the reader through the process of learning and creating data visualisation, following a unique journey with questions every step of the way, ultimately discussing how and when to bend and break the "rules" to come up with creative, unique, and sometimes unconventional ideas. Each easy-to-follow chapter poses one key question and provides a selection of discussion points and relevant data visualisation examples throughout. Structured in three parts: Section I poses questions around some fundamental data visualisation principles, while Section II introduces more advanced questions, challenging perceived best practices and suggesting when rules are open to interpretation or there to be broken. The questions in Section III introduce further themes leading on to specific ideas and visualisation projects in more detail. Questions in Dataviz: A Design-Driven Process for Data Visualisation will appeal to any reader with an interest in creative or unconventional data visualisation and will be especially useful for those at a beginner or intermediate level looking for inspiration and alternative ways to deploy their data visualisation skills outside of conventional business charts.
Queueing Theory 1: Advanced Trends
by Vladimir Anisimov Nikolaos LimniosThe aim of this book is to reflect the current cutting-edge thinking and established practices in the investigation of queueing systems and networks. This first volume includes ten chapters written by experts well-known in their areas. The book studies the analysis of queues with interdependent arrival and service times, characteristics of fluid queues, modifications of retrial queueing systems and finite-source retrial queues with random breakdowns, repairs and customers’ collisions. Some recent tendencies in the asymptotic analysis include the average and diffusion approximation of Markov queueing systems and networks, the diffusion and Gaussian limits of multi-channel queueing networks with rather general input flow, and the analysis of two-time-scale nonhomogenous Markov chains using the large deviations principle. The book also analyzes transient behavior of infinite-server queueing models with a mixed arrival process, the strong stability of queueing systems and networks, and applications of fast simulation methods for solving high-dimension combinatorial problems.
Queueing Theory 2: Advanced Trends
by Vladimir Anisimov Nikolaos LimniosThe aim of this book is to reflect the current cutting-edge thinking and established practices in the investigation of queueing systems and networks. This second volume includes eight chapters written by experts wellknown in their areas. The book conducts a stability analysis of certain types of multiserver regenerative queueing systems; a transient evaluation of Markovian queueing systems, focusing on closed-form distributions and numerical techniques; analysis of queueing models in service sectors using analytical and simulation approaches; plus an investigation of probability distributions in queueing models and their use in economics, industry, demography and environmental studies. This book also considers techniques for the control of information in queueing systems and their impact on strategic customer behavior, social welfare and the revenue of monopolists. In addition, applications of maximum entropy methods of inference for the analysis of a stable M/G/1 queue with heavy tails, and inventory models with positive service time - including perishable items and stock supplied using various algorithmic control policies ((s; S); (r;Q), etc.).
Queueing Theory and Network Applications: 14th International Conference, QTNA 2019, Ghent, Belgium, August 27–29, 2019, Proceedings (Lecture Notes in Computer Science #11688)
by Tuan Phung-Duc Shoji Kasahara Sabine WittevrongelThis book constitutes the proceedings of the 14th International Conference on Queueing Theory and Network Applications, QTNA 2019, held in Ghent, Belgium, in August 2019.The 23 full papers included in this volume were carefully reviewed and selected from 49 initial submissions. The papers are organized in topical sections on Retrial Queues; Controllable Queues; Strategic Queues; Queueing Networks; Scheduling Policies; Multidimensional Systems; and Queueing Models in Applications.
Queues
by D.R. CoxThis is a classic book on Queues. First published in 1961 it is clearly and concisely introduces the theory of queueing systems and is still just as relevant today. The monograph is aimed at both students and operational research workers concerned with the practical investigations of queueing, although almost every statistician will find its contents of interest.
Queues
by Moshe HavivQueueing theory (the mathematical theory of waiting lines in all its configurations) continues to be a standard major area of operations research on the stochastic side. Therefore, universities with an active program in operations research sometimes will have an entire course devoted mainly or entirely to queueing theory, and the course is also taught in computer science, electrical engineering, mathematics, and industrial engineering programs. The basic course in queueing theory is often taught at first year graduate level, though can be taught at senior level undergraduate as well. This text evolved from the author's preferred syllabus for teaching the course, presenting the material in a more logical order than other texts and so being more effective in teaching the basics of queueing theory. The first three chapters focus on the needed preliminaries, including exposition distributions, Poisson processes and generating functions, renewal theory, and Markov chains, Then, rather than switching to first-come first-served memoryless queues here as most texts do, Haviv discusses the M/G/1 model instead of the M/M/1, and then covers priority queues. Later chapters cover the G/M/1 model, thirteen examples of continuous-time Markov processes, open networks of memoryless queues and closed networks, queueing regimes with insensitive parameters, and then concludes with two-dimensional queueing models which are quasi birth and death processes. Each chapter ends with exercises.
Queues and Lévy Fluctuation Theory
by Krzysztof Dębicki Michel MandjesThe book provides an extensive introduction to queueing models driven by Lévy-processes as well as a systematic account of the literature on Lévy-driven queues. The objective is to make the reader familiar with the wide set of probabilistic techniques that have been developed over the past decades, including transform-based techniques, martingales, rate-conservation arguments, change-of-measure, importance sampling, and large deviations. On the application side, it demonstrates how Lévy traffic models arise when modelling current queueing-type systems (as communication networks) and includes applications to finance. Queues and Lévy Fluctuation Theory will appeal to postgraduate students and researchers in mathematics, computer science, and electrical engineering. Basic prerequisites are probability theory and stochastic processes.
Queuing Theory and Telecommunications
by Giovanni GiambeneThis book is aimed to provide a basic description of current networking technologies and protocols as well as to provide important tools for network performance analysis based on queuing theory. The second edition adds selected contents in the first part of the book for what concerns: (i) the token bucket regulator and traffic shaping issues; (ii) the TCP protocol congestion control that has a significant part in current networking; (iii) basic satellite networking issues; (iv) adding details on QoS support in IP networks. The book is organized so that we have first networking technologies and protocols (Part I) and then theory and exercises with applications to the different technologies and protocols (Part II). This book is intended as a textbook for master level courses in networking and telecommunications sectors.
Quick Calculus: A Self-Teaching Guide (Wiley Self-Teaching Guides)
by Daniel Kleppner Peter Dourmashkin Norman RamseyDiscover an accessible and easy-to-use guide to calculus fundamentals In Quick Calculus: A Self-Teaching Guide, 3rd Edition, a team of expert MIT educators delivers a hands-on and practical handbook to essential calculus concepts and terms. The author explores calculus techniques and applications, showing readers how to immediately implement the concepts discussed within to help solve real-world problems. In the book, readers will find: An accessible introduction to the basics of differential and integral calculus An interactive self-teaching guide that offers frequent questions and practice problems with solutions. A format that enables them to monitor their progress and gauge their knowledge This latest edition provides new sections, rewritten introductions, and worked examples that demonstrate how to apply calculus concepts to problems in physics, health sciences, engineering, statistics, and other core sciences. Quick Calculus: A Self-Teaching Guide, 3rd Edition is an invaluable resource for students and lifelong learners hoping to strengthen their foundations in calculus.
Quick Review Math Handbook Book 1
by Mcgraw-Hill StaffA handbook used to refresh your memory of mathematics concepts and skills.
¿Quién salta más? / Who Jumps More? (Storytelling Math)
by Grace Lin¡Libro de cartón grueso ahora disponible en español-inglés bilingüe! La ganadora del Honor de Caldecott, Grace Lin, celebra las matemáticas para todos los niños, ¡en todas partes!Board book now available in bilingual Spanish-English! Caldecott Honor winner Grace Lin celebrates math for every kid, everywhere!Olivia y Mei saltan en la nieve hasta llegar al árbol alto. Mei da unos saltos grandes como un reno. Olivia da muchos saltitos más pequeños como un conejo. Cada una salta "más" de manera diferente. Una exploración juguetona de la medición, la proporción y la amistad.Storytelling Math celebra a los niños usando las matemáticas en sus aventuras diarias mientras juegan, construyen y descubren el mundo que les rodea. Historias alegres y actividades manuales hacen que sea fácil para los niños y sus adultos explorar las matemáticas cotidianas juntos. Desarrollado en colaboración con expertos en matemáticas de TERC, una organización educativa con enfoque en ciencia, tecnología, ingeniería y matemáticas (STEM, por sus siglas en inglés), bajo una subvención de la Fundación Heising-Simons.Olivia and Mei jump in the snow all the way to the tall tree. Mei takes a few big leaps like a deer. Olivia makes lots of smaller hops like a bunny. Each jumps &“more&” in a different way. A playful exploration of measurement, proportion, and friendship.Storytelling Math celebrates children using math in their daily adventures as they play, build, and discover the world around them. Joyful stories and hands-on activities make it easy for kids and their grown-ups to explore everyday math together. Developed in collaboration with math experts at STEM education nonprofit TERC, under a grant from the Heising-Simons Foundation.
Quirky Quantum Concepts
by Eric L. MichelsenQuirky Quantum Concepts explains the more important and more difficult concepts in theoretical quantum mechanics, especially those which are consistently neglected or confusing in many common expositions. The emphasis is on physical understanding, which is necessary for the development of new, cutting edge science. In particular, this book explains the basis for many standard quantum methods, which are too often presented without sufficient motivation or interpretation. The book is not a simplification or popularization: it is real science for real scientists. Physics includes math, and this book does not shy away from it, but neither does it hide behind it. Without conceptual understanding, math is gibberish. The discussions here provide the experimental and theoretical reasoning behind some of the great discoveries, so the reader may see how discoveries arise from a rational process of thinking, a process which Quirky Quantum Concepts makes accessible to its readers. Quirky Quantum Concepts is therefore a supplement to almost any existing quantum mechanics text. Students and scientists will appreciate the combination of conversational style, which promotes understanding, with thorough scientific accuracy.
Quiver Representations
by Ralf SchifflerThis book is intended to serve as a textbook for a course in Representation Theory of Algebras at the beginning graduate level. The text has two parts. In Part I, the theory is studied in an elementary way using quivers and their representations. This is a very hands-on approach and requires only basic knowledge of linear algebra. The main tool for describing the representation theory of a finite-dimensional algebra is its Auslander-Reiten quiver, and the text introduces these quivers as early as possible. Part II then uses the language of algebras and modules to build on the material developed before. The equivalence of the two approaches is proved in the text. The last chapter gives a proof of Gabriel's Theorem. The language of category theory is developed along the way as needed.
R 4 Quick Syntax Reference: A Pocket Guide to the Language, API's and Library
by Margot TollefsonThis handy reference book detailing the intricacies of R covers version 4.x features, including numerous and significant changes to syntax, strings, reference counting, grid units, and more.Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the syntax required to make R work. You will find looking up the correct form for an expression quick and easy. Some of the new material includes information on RStudio, S4 syntax, working with character strings, and an example using the Twitter API.With a copy of the R 4 Quick Syntax Reference in hand, you will find that you are able to use the multitude of functions available in R and are even able to write your own functions to explore and analyze data.What You Will LearnDiscover the modes and classes of R objects and how to use themUse both packaged and user-created functions in R Import/export data and create new data objects in RCreate descriptive functions and manipulate objects in RTake advantage of flow control and conditional statementsWork with packages such as base, stats, and graphicsWho This Book Is ForThose with programming experience, either new to R, or those with at least some exposure to R but who are new to the latest version.
R Alles-in-einem-Band für Dummies (Für Dummies)
by Joseph SchmullerWenn Sie R von Grund auf kennenlernen und auch die fortgeschrittenen Techniken zur Lösung gängiger Aufgaben bei der Datenanalyse mit R beherrschen möchten, dann liegen Sie mit diesem Buch goldrichtig. Es bietet Ihnen nicht nur einen Überblick über die Programmierung in R und die Arbeit mit der Sprache, sondern geht auch auf die Arten von Projekten und Anwendungen ein, die R-Entwicklerinnen und -Entwickler häufig in Angriff nehmen müssen. Statistische Analysen, Datenvisualisierungen, maschinelles Lernen und Datenmanagement mit R: All das lernen Sie mit diesem Buch intensiv kennen.
R and MATLAB (Chapman & Hall/CRC The R Series)
by David E. HiebelerThe First Book to Explain How a User of R or MATLAB Can Benefit from the Other In today’s increasingly interdisciplinary world, R and MATLAB® users from different backgrounds must often work together and share code. R and MATLAB® is designed for users who already know R or MATLAB and now need to learn the other platform. The book makes the transition from one platform to the other as quick and painless as possible. Enables R and MATLAB Users to Easily Collaborate and Share Code The author covers essential tasks, such as working with matrices and vectors, writing functions and other programming concepts, graphics, numerical computing, and file input/output. He highlights important differences between the two platforms and explores common mistakes that are easy to make when transitioning from one platform to the other.
R Bioinformatics Cookbook: Use R and Bioconductor to perform RNAseq, genomics, data visualization, and bioinformatic analysis
by Dan MacLeanOver 60 recipes to model and handle real-life biological data using modern libraries from the R ecosystem Key Features Apply modern R packages to handle biological data using real-world examples Represent biological data with advanced visualizations suitable for research and publications Handle real-world problems in bioinformatics such as next-generation sequencing, metagenomics, and automating analyses Book Description Handling biological data effectively requires an in-depth knowledge of machine learning techniques and computational skills, along with an understanding of how to use tools such as edgeR and DESeq. With the R Bioinformatics Cookbook, you'll explore all this and more, tackling common and not-so-common challenges in the bioinformatics domain using real-world examples. This book will use a recipe-based approach to show you how to perform practical research and analysis in computational biology with R. You will learn how to effectively analyze your data with the latest tools in Bioconductor, ggplot, and tidyverse. The book will guide you through the essential tools in Bioconductor to help you understand and carry out protocols in RNAseq, phylogenetics, genomics, and sequence analysis. As you progress, you will get up to speed with how machine learning techniques can be used in the bioinformatics domain. You will gradually develop key computational skills such as creating reusable workflows in R Markdown and packages for code reuse. By the end of this book, you'll have gained a solid understanding of the most important and widely used techniques in bioinformatic analysis and the tools you need to work with real biological data. What you will learn Employ Bioconductor to determine differential expressions in RNAseq data Run SAMtools and develop pipelines to find single nucleotide polymorphisms (SNPs) and Indels Use ggplot to create and annotate a range of visualizations Query external databases with Ensembl to find functional genomics information Execute large-scale multiple sequence alignment with DECIPHER to perform comparative genomics Use d3.js and Plotly to create dynamic and interactive web graphics Use k-nearest neighbors, support vector machines and random forests to find groups and classify data Who this book is for This book is for bioinformaticians, data analysts, researchers, and R developers who want to address intermediate-to-advanced biological and bioinformatics problems by learning through a recipe-based approach. Working knowledge of R programming language and basic knowledge of bioinformatics are prerequisites.
The R Book
by Michael J. CrawleyHugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.This edition:Features full colour text and extensive graphics throughout.Introduces a clear structure with numbered section headings to help readers locate information more efficiently.Looks at the evolution of R over the past five years.Features a new chapter on Bayesian Analysis and Meta-Analysis.Presents a fully revised and updated bibliography and reference section.Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition:'...if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.' (The American Statistician, August 2008)'The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book...' (Professional Pensions, July 2007)
The R Book
by Elinor Jones Simon Harden Michael J. CrawleyA start-to-finish guide to one of the most useful programming languages for researchers in a variety of fields In the newly revised Third Edition of The R Book, a team of distinguished teachers and researchers delivers a user-friendly and comprehensive discussion of foundational and advanced topics in the R software language, which is used widely in science, engineering, medicine, economics, and other fields. The book is designed to be used as both a complete text—readable from cover to cover—and as a reference manual for practitioners seeking authoritative guidance on particular topics. This latest edition offers instruction on the use of the RStudio GUI, an easy-to-use environment for those new to R. It provides readers with a complete walkthrough of the R language, beginning at a point that assumes no prior knowledge of R and very little previous knowledge of statistics. Readers will also find: A thorough introduction to fundamental concepts in statistics and step-by-step roadmaps to their implementation in R; Comprehensive explorations of worked examples in R; A complementary companion website with downloadable datasets that are used in the book; In-depth examination of essential R packages. Perfect for undergraduate and postgraduate students of science, engineering, medicine economics, and geography, The R Book will also earn a place in the libraries of social sciences professionals.
R by Example (Use R!)
by Jim Albert Maria RizzoNow in its second edition, R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data. The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, it is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data, and this book is intended to be a useful resource for learning how to implement these procedures in R. The new edition includes expanded coverage of ggplot2 graphics, as well as new chapters on importing data and multivariate data methods.
R-Calculus, V: Description Logics (Perspectives in Formal Induction, Revision and Evolution)
by Wei Li Yuefei SuiThis book series consists of two parts, decidable description logics and undecidable description logics. It gives the R-calculi for description logics. This book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners in the field of logic.
R-Calculus, VI: Finite Injury Priority Method (Perspectives in Formal Induction, Revision and Evolution)
by Wei Li Yuefei SuiThis sixth volume of the book series applies finite injury priority method to R-calculi and obtain (in)completeness theorem for binary-valued, Post three-valued, B2^2-valued and L4-valued first-order logics, and extend the method to infinite injury priority method and 0"-method for default logic to produce pseudo-extensions of a default theory, corresponding to different R-calculi. Finite injury priority method and tree constructions are discussed in this book. This book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners in the field of logic.
An R Companion for Applied Statistics I: Basic Bivariate Techniques
by Danney RascoAn R Companion for Applied Statistics I: Basic Bivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use it. R is a powerful, flexible, and free tool. However, the flexibility—which eventually becomes a great asset—can make the initial learning curve appear steep. This book introduces a few key aspects of the R tool. As readers become comfortable with these aspects, they develop a foundation from which to more thoroughly explore R and the packages available for it. This introduction does not explain every possible way to analyze data or perform a specific type of analysis. Rather, it focuses on the analyses that are traditionally included in an undergraduate statistics course and provides one or two ways to run these analyses in R. Datasets and scripts to run the examples are provided on an accompanying website. The book has been designed to be an R companion to Warner′s Applied Statistics I, Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide, without reference to the Warner text.
An R Companion for Applied Statistics I: Basic Bivariate Techniques
by Danney RascoAn R Companion for Applied Statistics I: Basic Bivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use it. R is a powerful, flexible, and free tool. However, the flexibility—which eventually becomes a great asset—can make the initial learning curve appear steep. This book introduces a few key aspects of the R tool. As readers become comfortable with these aspects, they develop a foundation from which to more thoroughly explore R and the packages available for it. This introduction does not explain every possible way to analyze data or perform a specific type of analysis. Rather, it focuses on the analyses that are traditionally included in an undergraduate statistics course and provides one or two ways to run these analyses in R. Datasets and scripts to run the examples are provided on an accompanying website. The book has been designed to be an R companion to Warner′s Applied Statistics I, Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide, without reference to the Warner text.
An R Companion for Applied Statistics II: Multivariable and Multivariate Techniques
by Danney RascoAn R Companion for Applied Statistics II: Multivariable and Multivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use R to analyze multivariate data. The book focuses on the statistics generally covered in an intermediate or multivariate statistics course and provides one or two ways to run each analysis in R. The book has been designed to be an R companion to Rebecca M. Warner′s Applied Statistics II: Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide for a multivariate statistics course, without reference to the Warner text. Datasets and scripts to run the examples are provided on an accompanying website.