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Graphics for Statistics and Data Analysis with R (Chapman & Hall/CRC Texts in Statistical Science)
by Kevin J. Keen<i>Graphics for Statistics and Data Analysis with R, Second Edition</i>, presents the basic principles of graphical design and applies these principles to engaging examples using the graphics and lattice packages in R. It offers a wide array of modern graphical displays for data visualization and representation. Added in the second edition are coverage of the ggplot2 graphics package, material on human visualization and color rendering in R, on screen, and in print.
Graphics for Statistics and Data Analysis with R (Chapman & Hall/CRC Texts in Statistical Science)
by Kevin J. Keen<p>Graphics for Statistics and Data Analysis with R, Second Edition, presents the basic principles of graphical design and applies these principles to engaging examples using the graphics and lattice packages in R. It offers a wide array of modern graphical displays for data visualization and representation. Added in the second edition are coverage of the ggplot2 graphics package, material on human visualization and color rendering in R, on screen, and in print. It emphasizes the fundamentals of statistical graphics and best practice guidelines for producing and choosing among graphical displays in R. <p>Provides downloadable R code and data for figures at www.graphicsforstatistics.com</p>
Graphs in Perturbation Theory: Algebraic Structure And Asymptotics (Springer Theses)
by Michael BorinskyThis book is the first systematic study of graphical enumeration and the asymptotic algebraic structures in perturbative quantum field theory. Starting with an exposition of the Hopf algebra structure of generic graphs, it reviews and summarizes the existing literature. It then applies this Hopf algebraic structure to the combinatorics of graphical enumeration for the first time, and introduces a novel method of asymptotic analysis to answer asymptotic questions. This major breakthrough has combinatorial applications far beyond the analysis of graphical enumeration. The book also provides detailed examples for the asymptotics of renormalizable quantum field theories, which underlie the Standard Model of particle physics. A deeper analysis of such renormalizable field theories reveals their algebraic lattice structure. The pedagogical presentation allows readers to apply these new methods to other problems, making this thesis a future classic for the study of asymptotic problems in quantum fields, network theory and far beyond.
Great Circles: The Transits of Mathematics and Poetry (Mathematics, Culture, and the Arts)
by Emily Rolfe GrosholzThis volume explores the interaction of poetry and mathematics by looking at analogies that link them. The form that distinguishes poetry from prose has mathematical structure (lifting language above the flow of time), as do the thoughtful ways in which poets bring the infinite into relation with the finite. The history of mathematics exhibits a dramatic narrative inspired by a kind of troping, as metaphor opens, metonymy and synecdoche elaborate, and irony closes off or shifts the growth of mathematical knowledge. The first part of the book is autobiographical, following the author through her discovery of these analogies, revealed by music, architecture, science fiction, philosophy, and the study of mathematics and poetry. The second part focuses on geometry, the circle and square, launching us from Shakespeare to Housman, from Euclid to Leibniz. The third part explores the study of dynamics, inertial motion and transcendental functions, from Descartes to Newton, and in 20th c. poetry. The final part contemplates infinity, as it emerges in modern set theory and topology, and in contemporary poems, including narrative poems about modern cosmology.
The Great Leveler: Violence and the History of Inequality from the Stone Age to the Twenty-First Century (The Princeton Economic History of the Western World #114)
by Walter ScheidelAre mass violence and catastrophes the only forces that can seriously decrease economic inequality? To judge by thousands of years of history, the answer is yes. Tracing the global history of inequality from the Stone Age to today, Walter Scheidel shows that it never dies peacefully. The Great Leveler is the first book to chart the crucial role of violent shocks in reducing inequality over the full sweep of human history around the world. The “Four Horsemen” of leveling—mass-mobilization warfare, transformative revolutions, state collapse, and catastrophic plagues—have repeatedly destroyed the fortunes of the rich. Today, the violence that reduced inequality in the past seems to have diminished, and that is a good thing. But it casts serious doubt on the prospects for a more equal future. An essential contribution to the debate about inequality, The Great Leveler provides important new insights about why inequality is so persistent—and why it is unlikely to decline anytime soon.
Grid Optimal Integration of Electric Vehicles: Examples with Matlab Implementation
by Seddik Bacha Andrés Ovalle Ahmad HablyThis book is a compilation of recent research on distributed optimization algorithms for the integral load management of plug-in electric vehicle (PEV) fleets and their potential services to the electricity system. It also includes detailed developed Matlab scripts. These algorithms can be implemented and extended to diverse applications where energy management is required (smart buildings, railways systems, task sharing in micro-grids, etc.). The proposed methodologies optimally manage PEV fleets’ charge and discharge schedules by applying classical optimization, game theory, and evolutionary game theory techniques. Taking owner’s requirements into consideration, these approaches provide services like load shifting, load balancing among phases of the system, reactive power supply, and task sharing among PEVs. The book is intended for use in graduate optimization and energy management courses, and readers are encouraged to test and adapt the scripts to their specific applications.
Group Decision and Negotiation in an Uncertain World: 18th International Conference, GDN 2018, Nanjing, China, June 9-13, 2018, Proceedings (Lecture Notes in Business Information Processing #315)
by Ye Chen Gregory Kersten Rudolf Vetschera Haiyan XuThis book constitutes the refereed proceedings of the 18th International Conference on Group Decision and Negotiation, GDN 2018, held in Nanjing, China, in June 2018. The field of Group Decision and Negotiation focuses on decision processes with at least two participants and a common goal but conflicting individual goals. Research areas of Group Decision and Negotiation include electronic negotiations, experiments, the role of emotions in group decision and negotiations, preference elicitation and decision support for group decisions and negotiations, and conflict resolution principles.The 15 full papers presented in this volume were carefully reviewed and selected from 143 submissions. They were organized in topical sections named: theoretical concepts of group decision and negotiation; decision support and behavior in group decision and negotiation; and applications of group decision and negotiations.
Groups, Matrices, and Vector Spaces: A Group Theoretic Approach to Linear Algebra
by James B. CarrellTo emphasize the importance of a foundation of knowledge in both geometry and algebra, this text includes an introduction to Euclidean Spaces, and a brief treatment of algebraic topics such as matrix algebra, linear systems, vector spaces, linear coding theory, determinants, eigentheory, group theory, ring theory, and field extensions, even covering an introduction to cryptography.
The Growth Delusion: Why Economists Are Getting It Wrong And What We Can Do About It
by David PillingA provocative critique of the pieties and fallacies of our obsession with economic growth We live in a society in which a priesthood of economists, wielding impenetrable mathematical formulas, set the framework for public debate. Ultimately, it is the perceived health of the economy which determines how much we can spend on our schools, highways, and defense; economists decide how much unemployment is acceptable and whether it is right to print money or bail out profligate banks. The backlash we are currently witnessing suggests that people are turning against the experts and their faulty understanding of our lives. Despite decades of steady economic growth, many citizens feel more pessimistic than ever, and are voting for candidates who voice undisguised contempt for the technocratic elite. For too long, economics has relied on a language which fails to resonate with people's actual experience, and we are now living with the consequences. In this powerful, incisive book, David Pilling reveals the hidden biases of economic orthodoxy and explores the alternatives to GDP, from measures of wealth, equality, and sustainability to measures of subjective wellbeing. Authoritative, provocative, and eye-opening, The Growth Delusion offers witty and unexpected insights into how our society can respond to the needs of real people instead of pursuing growth at any cost.
Grundkurs Theoretische Physik 1: Klassische Mechanik (Springer-Lehrbuch)
by Wolfgang NoltingDer Grundkurs Theoretische Physik deckt in sieben Bänden alle für Diplom- und Bachelor/Master-Studiengänge maßgeblichen Gebiete ab. Jeder Band vermittelt das im jeweiligen Semester nötige theoretisch-physikalische Rüstzeug. Übungsaufgaben mit ausführlichen Lösungen dienen der Vertiefung des Stoffs. Band 1 behandelt die klassische Mechanik. Vorausgesetzt wird nur die übliche Schulmathematik, andere mathematische Hilfsmittel werden zu Beginn ausführlich erläutert. Die zweifarbig gestaltete Neuauflage wurde grundlegend überarbeitet und ergänzt.
Grundlagen der Differenzialgleichungen für Dummies (Für Dummies)
by Timm SiggDifferenzialgleichungen sind Ihnen ein Buch mit sieben Siegeln? Kein Problem! Im ersten Teil liefert Ihnen dieses Buch wirklich alles, was Sie an Handwerkszeug zum Lösen von Differenzialgleichungen benötigen. Anschließend erfahren Sie, was Differenzialgleichungen überhaupt sind und mit welchen Methoden man sie lösen kann. Im dritten Teil wird es ernst: Sie werden einfache Differenzialgleichungen rechnerisch lösen. Aber keine Sorge: Vielfältige Beispiele geben Ihnen die Gelegenheit, die Verfahren gründlich zu üben. Und damit Sie wissen, warum Sie sich all diesen Mühen unterziehen, werden Sie zuletzt auf berühmte Differenzialgleichungen aus Biologie, Chemie, Physik und Ökonomie treffen.
Grundlagen der elektromagnetischen Feldtheorie: Maxwellgleichungen, Lösungsmethoden und Anwendungen
by Harald KlingbeilDie Konzeption und Stoffauswahl dieser Einführung in die mathematischen Grundlagen der elektromagnetischen Feldtheorie stellt die Verbindung zwischen Elektrotechnik, Mathematik und Physik her. Umfassend, mathematisch präzise und dennoch leicht verständlich gelingt dem Leser mit Hilfe dieses Buchs der behutsame Einstieg in die Tensoranalysis und die Grundlagen der speziellen Relativitätstheorie sowie in die invariante Darstellung der Maxwellgleichungen.
Grundzüge der Globalen Optimierung
by Oliver SteinDas vorliegende Lehrbuch ist eine Einführung in die globale Optimierung, die mathematische Sachverhalte einerseits stringent behandelt, sie aber andererseits auch sehr ausführlich motiviert und mit 75 Abbildungen illustriert. Das Buch richtet sich daher nicht nur an Mathematiker, sondern auch an Natur-, Ingenieur- und Wirtschaftswissenschaftler, die mathematisch fundierte Verfahren in ihrem Gebiet verstehen und anwenden möchten. Mit fast zweihundert Seiten stellt das Buch genügend Auswahlmöglichkeiten zur Verfügung, um es als Grundlage für unterschiedlich angelegte Vorlesungen zur globalen Optimierung zu verwenden. Die ausführliche Behandlung der globalen Lösbarkeit von Optimierungsproblemen unter anwendungsrelevanten Voraussetzungen setzt dabei einen neuen Akzent, der den Bestand der bisherigen Lehrbücher zur Optimierung bereichert. Anhand von Theorie und Algorithmen der glatten konvexen Optimierung verdeutlicht das Buch, dass die globale Lösung einer in der Praxis häufig auftretenden Klasse von Optimierungsproblemen effizient möglich ist, während es für die schwerer handhabbaren nichtkonvexen Probleme ausführlich die Ideen von Branch-and-Bound-Verfahren entwickelt.
Grundzüge der Nichtlinearen Optimierung
by Oliver SteinDas vorliegende Lehrbuch ist eine Einführung in die nichtlineare Optimierung, die mathematische Sachverhalte einerseits stringent behandelt, sie aber andererseits auch sehr ausführlich motiviert und mit 39 Abbildungen illustriert. Das Buch richtet sich daher nicht nur an Mathematiker, sondern auch an Natur-, Ingenieur- und Wirtschaftswissenschaftler, die mathematisch fundierte Verfahren in ihrem Gebiet verstehen und anwenden möchten. Mit fast zweihundert Seiten stellt das Buch genügend Auswahlmöglichkeiten zur Verfügung, um es als Grundlage für unterschiedlich angelegte Vorlesungen zur nichtlinearen Optimierung zu verwenden. Viele geometrische Ansätze für das Verständnis sowohl von Optimalitätsbedingungen als auch von numerischen Verfahren setzen dabei einen neuen Akzent, der den Bestand der bisherigen Lehrbücher zur Optimierung bereichert. Dies betrifft insbesondere die ausführliche Behandlung der Probleme, die durch verschiedene funktionale Beschreibungen derselben Geometrie der Menge zulässiger Punkte entstehen können, und die dadurch motivierte Einführung von Constraint Qualifications für die Herleitung ableitungsbasierter Optimalitätsbedingungen.
A Guide to Business Statistics
by David M. McEvoyAn accessible text that explains fundamental concepts in business statistics that are often obscured by formulae and mathematical notation A Guide to Business Statistics offers a practical approach to statistics that covers the fundamental concepts in business and economics. The book maintains the level of rigor of a more conventional textbook in business statistics but uses a more streamlined and intuitive approach. In short, A Guide to Business Statistics provides clarity to the typical statistics textbook cluttered with notation and formulae. The author—an expert in the field—offers concise and straightforward explanations to the core principles and techniques in business statistics. The concepts are introduced through examples, and the text is designed to be accessible to readers with a variety of backgrounds. To enhance learning, most of the mathematical formulae and notation appears in technical appendices at the end of each chapter. This important resource: • Offers a comprehensive guide to understanding business statistics targeting business and economics students and professionals • Introduces the concepts and techniques through concise and intuitive examples • Focuses on understanding by moving distracting formulae and mathematical notation to appendices • Offers intuition, insights, humor, and practical advice for students of business statistics • Features coverage of sampling techniques, descriptive statistics, probability, sampling distributions, confidence intervals, hypothesis tests, and regression Written for undergraduate business students, business and economics majors, teachers, and practitioners, A Guide to Business Statistics offers an accessible guide to the key concepts and fundamental principles in statistics.DAVID M. McEVOY, PhD, is an Associate Professor in the Economics Department at Appalachian State University in Boone NC. He has published over 20 peer-reviewed articles and is coeditor of two books. Dr. McEvoy is an award-winning educator who has taught undergraduate courses in business statistics for over 10 years. DAVID M. McEVOY, PhD, is an Associate Professor in the Economics Department at Appalachian State University in Boone NC. He has published over 20 peer-reviewed articles and is coeditor of two books. Dr. McEvoy is an award-winning educator who has taught undergraduate courses in business statistics for over 10 years.An accessible text that explains fundamental concepts in business statistics that are often obscured by formulae and mathematical notation A Guide to Business Statistics offers a practical approach to statistics that covers the fundamental concepts in business and economics. The book maintains the level of rigor of a more conventional textbook in business statistics but uses a more streamlined and intuitive approach. In short, A Guide to Business Statistics provides clarity to the typical statistics textbook cluttered with notation and formulae. The author—an expert in the field—offers concise and straightforward explanations to the core principles and techniques in business statistics. The concepts are introduced through examples, and the text is designed to be accessible
A Guide to Outcome Modeling In Radiotherapy and Oncology: Listening to the Data (Series in Medical Physics and Biomedical Engineering)
by Issam El NaqaThis book explores outcome modeling in cancer from a data-centric perspective to enable a better understanding of complex treatment response, to guide the design of advanced clinical trials, and to aid personalized patient care and improve their quality of life. It contains coverage of the relevant data sources available for model construction (panomics), ranging from clinical or preclinical resources to basic patient and treatment characteristics, medical imaging (radiomics), and molecular biological markers such as those involved in genomics, proteomics and metabolomics. It also includes discussions on the varying methodologies for predictive model building with analytical and data-driven approaches. This book is primarily intended to act as a tutorial for newcomers to the field of outcome modeling, as it includes in-depth how-to recipes on modeling artistry while providing sufficient instruction on how such models can approximate the physical and biological realities of clinical treatment. The book will also be of value to seasoned practitioners as a reference on the varying aspects of outcome modeling and their current applications. Features: Covers top-down approaches applying statistical, machine learning, and big data analytics and bottom-up approaches using first principles and multi-scale techniques, including numerical simulations based on Monte Carlo and automata techniques Provides an overview of the available software tools and resources for outcome model development and evaluation, and includes hands-on detailed examples throughout Presents a diverse selection of the common applications of outcome modeling in a wide variety of areas: treatment planning in radiotherapy, chemotherapy and immunotherapy, utility-based and biomarker applications, particle therapy modeling, oncological surgery, and the design of adaptive and SMART clinical trials
Guide to Programming for the Digital Humanities: Lessons For Introductory Python (SpringerBriefs in Computer Science)
by Brian KokenspargerAs an introduction to programming for the Digital Humanities (DH), this book presents six key assignments oriented on DH topics. The topics include Computing Change Over Time (calculating burials at a historic cemetery), Visualizing Change Over Time (visualizing the burials at the historic cemetery), Textual Analysis (finding word frequencies and “stop words” in public domain texts), XML Transformation (transforming a simplified version of XML into HTML styled with CSS), Stylometry (comparing the measured features of graphic images), and Social Network Analysis (analyzing extended relationships in historic circles). The book focuses on the practical application of these assignments in the classroom, providing a range of variations for each assignment, which can be selected on the basis of students’ specific programming background and skills; “atomic” assignments, which can be used to give students the experience they need to successfully complete the main assignments; and some common pitfalls and gotchas to manage in the classroom. The book’s chief goals are to introduce novice computer science (CS) students to programming for DH, and to offer them valuable hands-on experience with core programming concepts.
Handbook of Approximation Algorithms and Metaheuristics: Contemporary and Emerging Applications, Volume 2 (Chapman & Hall/CRC Computer and Information Science Series)
by Teofilo F. GonzalezHandbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems. Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more. About the Editor Teofilo F. Gonzalez is a professor emeritus of computer science at the University of California, Santa Barbara. He completed his Ph.D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma, the Pennsylvania State University, and the University of Texas at Dallas, before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of job scheduling, graph algorithms, computational geometry, message communication, wire routing, etc.
Handbook of Approximation Algorithms and Metaheuristics: Methologies and Traditional Applications, Volume 1 (Chapman & Hall/CRC Computer and Information Science Series)
by Teofilo F. GonzalezHandbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems. Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more. About the Editor Teofilo F. Gonzalez is a professor emeritus of computer science at the University of California, Santa Barbara. He completed his Ph.D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma, the Pennsylvania State University, and the University of Texas at Dallas, before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of job scheduling, graph algorithms, computational geometry, message communication, wire routing, etc.
Handbook of Big Data Analytics (Springer Handbooks Of Computational Statistics Ser.)
by Xiaotong Shen Henry Horng-Shing Lu Wolfgang Karl HärdleAddressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.
Handbook of Data Structures and Applications (Chapman & Hall/CRC Computer and Information Science Series)
by Dinesh P. Mehta and Sartaj SahniThe Handbook of Data Structures and Applications was first published over a decade ago. This second edition aims to update the first by focusing on areas of research in data structures that have seen significant progress. While the discipline of data structures has not matured as rapidly as other areas of computer science, the book aims to update those areas that have seen advances. Retaining the seven-part structure of the first edition, the handbook begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next analyze miscellaneous data structures, which are well-known structures that elude easy classification. The book then addresses mechanisms and tools that were developed to facilitate the use of data structures in real programs. It concludes with an examination of the applications of data structures. Four new chapters have been added on Bloom Filters, Binary Decision Diagrams, Data Structures for Cheminformatics, and Data Structures for Big Data Stores, and updates have been made to other chapters that appeared in the first edition.The Handbook is invaluable for suggesting new ideas for research in data structures, and for revealing application contexts in which they can be deployed. Practitioners devising algorithms will gain insight into organizing data, allowing them to solve algorithmic problems more efficiently.
Handbook of Discrete and Combinatorial Mathematics (Discrete Mathematics and Its Applications)
by Kenneth H. RosenHandbook of Discrete and Combinatorial Mathematics provides a comprehensive reference volume for mathematicians, computer scientists, engineers, as well as students and reference librarians. The material is presented so that key information can be located and used quickly and easily. Each chapter includes a glossary. Individual topics are covered in sections and subsections within chapters, each of which is organized into clearly identifiable parts: definitions, facts, and examples. Examples are provided to illustrate some of the key definitions, facts, and algorithms. Some curious and entertaining facts and puzzles are also included. Readers will also find an extensive collection of biographies. This second edition is a major revision. It includes extensive additions and updates. Since the first edition appeared in 1999, many new discoveries have been made and new areas have grown in importance, which are covered in this edition.
Handbook of Discrete and Computational Geometry (Discrete Mathematics and Its Applications)
by Csaba D. Toth Joseph O'Rourke Jacob E. GoodmanThe Handbook of Discrete and Computational Geometry is intended as a reference book fully accessible to nonspecialists as well as specialists, covering all major aspects of both fields. <P><P>The book offers the most important results and methods in discrete and computational geometry to those who use them in their work, both in the academic world—as researchers in mathematics and computer science—and in the professional world—as practitioners in fields as diverse as operations research, molecular biology, and robotics. <P><P>Discrete geometry has contributed significantly to the growth of discrete mathematics in recent years. This has been fueled partly by the advent of powerful computers and by the recent explosion of activity in the relatively young field of computational geometry. This synthesis between discrete and computational geometry lies at the heart of this Handbook. <P><P>A growing list of application fields includes combinatorial optimization, computer-aided design, computer graphics, crystallography, data analysis, error-correcting codes, geographic information systems, motion planning, operations research, pattern recognition, robotics, solid modeling, and tomography.
Handbook of Dynamic Game Theory
by Georges Zaccour Tamer BaşarThis will be a two-part handbook on Dynamic Game Theory and part of the Springer Reference program. Part I will be on the fundamentals and theory of dynamic games. It will serve as a quick reference and a source of detailed exposure to topics in dynamic games for a broad community of researchers, educators, practitioners, and students. Each topic will be covered in 2-3 chapters with one introducing basic theory and the other one or two covering recent advances and/or special topics. Part II will be on applications in fields such as economics, management science, engineering, biology, and the social sciences.
Handbook of Educational Measurement and Psychometrics Using R (Chapman & Hall/CRC The R Series)
by Christopher D. Desjardins Okan BulutCurrently there are many introductory textbooks on educational measurement and psychometrics as well as R. However, there is no single book that covers important topics in measurement and psychometrics as well as their applications in R. The Handbook of Educational Measurement and Psychometrics Using R covers a variety of topics, including classical test theory; generalizability theory; the factor analytic approach in measurement; unidimensional, multidimensional, and explanatory item response modeling; test equating; visualizing measurement models; measurement invariance; and differential item functioning.This handbook is intended for undergraduate and graduate students, researchers, and practitioners as a complementary book to a theory-based introductory or advanced textbook in measurement. Practitioners and researchers who are familiar with the measurement models but need to refresh their memory and learn how to apply the measurement models in R, would find this handbook quite fulfilling. Students taking a course on measurement and psychometrics will find this handbook helpful in applying the methods they are learning in class. In addition, instructors teaching educational measurement and psychometrics will find our handbook as a useful supplement for their course.