Praise for the First Edition ". . . [this book] should be on the shelf of everyone interested in . . . longitudinal data analysis." —Journal of the American Statistical Association Features newly developed topics and applications of the analysis of longitudinal data Applied Longitudinal Analysis, Second Edition presents modern methods for analyzing data from longitudinal studies and now features the latest state-of-the-art techniques. The book emphasizes practical, rather than theoretical, aspects of methods for the analysis of diverse types of longitudinal data that can be applied across various fields of study, from the health and medical sciences to the social and behavioral sciences. The authors incorporate their extensive academic and research experience along with various updates that have been made in response to reader feedback. The Second Edition features six newly added chapters that explore topics currently evolving in the field, including: Fixed effects and mixed effects models Marginal models and generalized estimating equations Approximate methods for generalized linear mixed effects models Multiple imputation and inverse probability weighted methods Smoothing methods for longitudinal data Sample size and power Each chapter presents methods in the setting of applications to data sets drawn from the health sciences. New problem sets have been added to many chapters, and a related website features sample programs and computer output using SAS, Stata, and R, as well as data sets and supplemental slides to facilitate a complete understanding of the material. With its strong emphasis on multidisciplinary applications and the interpretation of results, Applied Longitudinal Analysis, Second Edition is an excellent book for courses on statistics in the health and medical sciences at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for researchers and professionals in the medical, public health, and pharmaceutical fields as well as those in social and behavioral sciences who would like to learn more about analyzing longitudinal data.
Basic Analysis IV: Measure Theory and Integration introduces students to concepts from measure theory and continues their training in the abstract way of looking at the world. This is a most important skill to have when your life's work will involve quantitative modeling to gain insight into the real world. This text generalizes the notion of integration to a very abstract setting in a variety of ways. We generalize the notion of the length of an interval to the measure of a set and learn how to construct the usual ideas from integration using measures. We discuss carefully the many notions of convergence that measure theory provides. Features • Can be used as a traditional textbook as well as for self-study • Suitable for advanced students in mathematics and associated disciplines • Emphasises learning how to understand the consequences of assumptions using a variety of tools to provide the proofs of propositions
This title gives students a good understanding of how quantum mechanics describes the material world. The text stresses the continuity between the quantum world and the classical world, which is merely an approximation to the quantum world.
Ein Wiley-Klassiker über Bayes-Statistik, jetzt in durchgesehener und erweiterter Neuauflage! - Werk spiegelt die stürmische Entwicklung dieses Gebietes innerhalb der letzten Jahre wider - vollständige Darstellung der theoretischen Grundlagen - jetzt ergänzt durch unzählige Anwendungsbeispiele - die wichtigsten modernen Methoden (u. a. hierarchische Modellierung, linear-dynamische Modellierung, Metaanalyse, MCMC-Simulationen) - einzigartige Diskussion der Finetti-Transformierten und anderer Themen, über die man ansonsten nur spärliche Informationen findet - Lösungen zu den Übungsaufgaben sind enthalten
Game theory is the mathematical analysis of strategic interaction. In the fifty years since the appearance of von Neumann and Morgenstern's classic Theory of Games and Economic Behavior (Princeton, 1944), game theory has been widely applied to problems in economics. Until recently, however, its usefulness in political science has been underappreciated, in part because of the technical difficulty of the methods developed by economists. James Morrow's book is the first to provide a standard text adapting contemporary game theory to political analysis. It uses a minimum of mathematics to teach the essentials of game theory and contains problems and their solutions suitable for advanced undergraduate and graduate students in all branches of political science. Morrow begins with classical utility and game theory and ends with current research on repeated games and games of incomplete information. The book focuses on noncooperative game theory and its application to international relations, political economy, and American and comparative politics. Special attention is given to models of four topics: bargaining, legislative voting rules, voting in mass elections, and deterrence. An appendix reviews relevant mathematical techniques. Brief bibliographic essays at the end of each chapter suggest further readings, graded according to difficulty. This rigorous but accessible introduction to game theory will be of use not only to political scientists but also to psychologists, sociologists, and others in the social sciences.
This book explores the subject of artificial psychology from the standpoint of how online Chatbots have infiltrated and affected societies and the world in general. The book explores the psychological effects of depending on an online entity for our needs – even if it’s a reminder of scheduled events. The author provides insight into the notion of human-Chatbot exchanges, understanding, and false emotions both from the Chatbot and from the human. He goes on to investigate and discuss the dangers of too much reliance on technology that learns from a variety of sources and how some sources can negatively influence Chatbots, and by doing so, negatively affect people. The book also discusses human-Chatbot interactions and the natural language interface(s) required to respond adequately to humans. Lastly, the author explores the notion of ethical considerations for people, based on their interactions with Chatbots, including information based on cultural differences between different regions of the world.
The book provides a bridge from courses in general physics to the intermediate-level courses in classical mechanics, electrodynamics and quantum mechanics. The author bases the mathematical discussions on specific physical problems to provide a basis for developing mathematical intuition.
Introduces the major elements of semantics in a simple, step-by-step fashion. Sections of explanation and examples are followed by practice exercises with answers and comment provided.
Understand the fundamentals of applied mathematics with this up-to-date introduction Applied mathematics is the use of mathematical concepts and methods in various applied or practical areas, including engineering, computer science, and more. As engineering science expands, the ability to work from mathematical principles to solve and understand equations has become an ever more critical component of engineering fields. New engineering processes and materials place ever-increasing mathematical demands on new generations of engineers, who are looking more and more to applied mathematics for an expanded toolkit. Applied Mathematics and Modeling for Chemical Engineers provides this toolkit in a comprehensive and easy-to-understand introduction. Combining classical analysis of modern mathematics with more modern applications, it offers everything required to assess and solve mathematical problems in chemical engineering. Now updated to reflect contemporary best practices and novel applications, this guide promises to situate readers in a 21st century chemical engineering field in which direct knowledge of mathematics is essential. Readers of the third edition of Applied Mathematics and Modeling for Chemical Engineers will also find: Detailed treatment of ordinary differential equations (ODEs) and partial differential equations (PDEs) and their solutions New material concerning approximate solution methods like perturbation techniques and elementary numerical solutions Two new chapters dealing with Linear Algebra and Applied Statistics Applied Mathematics and Modeling for Chemical Engineers is ideal for graduate and advanced undergraduate students in chemical engineering and related fields, as well as instructors and researchers seeking a handy reference.
Adaptive Stochastic Optimization Techniques with Applications provides a single, convenient source for state-of-the-art information on optimization techniques used to solve problems with adaptive, dynamic, and stochastic features. Presenting modern advances in static and dynamic optimization, decision analysis, intelligent systems, evolutionary pro
Students of topology rightly complain that much of the basic material in the subject cannot easily be found in the literature, at least not in a convenient form. In this book I have tried to take a fresh look at some of this basic material and to organize it in a coherent fashion. The text is as self-contained as I could reasonably make it and should be quite accessible to anyone who has an elementary knowledge of point-set topology and group theory. This book is based on a course of 16 graduate lectures given at Oxford and elsewhere from time to time. In a course of that length one cannot discuss too many topics without being unduly superficial. However, this was never intended as a treatise on the subject but rather as a short introductory course which will, I hope, prove useful to specialists and non-specialists alike. The introduction contains a description of the contents. No algebraic or differen tial topology is involved, although I have borne in mind the needs of students of those branches of the subject. Exercises for the reader are scattered throughout the text, while suggestions for further reading are contained in the lists of references at the end of each chapter. In most cases these lists include the main sources I have drawn on, but this is not the type of book where it is practicable to give a reference for everything.
Numerical Methods with VBA Programming provides a unique and unified treatment of numerical methods and VBA computer programming, topics that naturally support one another within the study of engineering and science. This engaging text incorporates real-world scenarios to motivate technical material, helping students understand and retain difficult and key concepts. Such examples include comparing a two-point boundary value problem to determining when you should leave for the airport to catch a scheduled flight. Numerical examples are accompanied by closed-form solutions to demonstrate their correctness. Within the programming sections, tips are included that go beyond language basics to make programming more accessible for students. A unique section suggest ways in which the starting values for non-linear equations may be estimated. Flow charts for many of the numerical techniques discussed provide general guidance to students without revealing all of the details. Useful appendices provide summaries of Excel and VBA commands, Excel functions accessible in VBA, basics of differentiation, and more!
During the past decade, the science of dynamic meteorology has continued its rapid advance. The scope of dynamic meteorology has broadened considerably. Much of the material is based on a two-term course for seniors majoring in atmospheric sciences. This book presents a cogent explanation of the fundamentals of meteorology and explains storm dynamics for weather-oriented meteorologists. It discusses climate dynamics and the implications posed for global change. The new edition has added a companion website with MATLAB exercises and updated treatments of several key topics. Provides clear physical explanations of key dynamical principles Contains a wealth of illustrations to elucidate text and equations, plus end-of-chapter problems Holton is one of the leading authorities in contemporary meteorology, and well known for his clear writing style Instructor's Manual available to adopters NEW IN THIS EDITION A companion website with MATLAB® exercises and demonstrations Updated treatments on climate dynamics, tropical meteorology, middle atmosphere dynamics, and numerical prediction
...this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian statistics. The authors continue to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for discrete random variables, binomial proportions, Poisson, and normal means, and simple linear regression. In addition, more advanced topics in the field are presented in four new chapters: Bayesian inference for a normal with unknown mean and variance; Bayesian inference for a Multivariate Normal mean vector; Bayesian inference for the Multiple Linear Regression Model; and Computational Bayesian Statistics including Markov Chain Monte Carlo. The inclusion of these topics will facilitate readers' ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. Minitab macros and R functions are available on the book's related website to assist with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: Topics including the Joint Likelihood function and inference using independent Jeffreys priors and join conjugate prior The cutting-edge topic of computational Bayesian Statistics in a new chapter, with a unique focus on Markov Chain Monte Carlo methods Exercises throughout the book that have been updated to reflect new applications and the latest software applications Detailed appendices that guide readers through the use of R and Minitab software for Bayesian analysis and Monte Carlo simulations, with all related macros available on the book's website Introduction to Bayesian Statistics, Third Edition is a textbook for upper-undergraduate or first-year graduate level courses on introductory statistics course with a Bayesian emphasis. It can also be used as a reference work for statisticians who require a working knowledge of Bayesian statistics.
Detailed coverage of probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.
Easily accessible and clinically focused, Abeloff's Clinical Oncology, 6th Edition, covers recent advances in our understanding of the pathophysiology of cancer, cellular and molecular causes of cancer initiation and progression, new and emerging therapies, current trials, and much more. Masterfully authored by an international team of leading cancer experts, it offers clear, practical coverage of everything from basic science to multidisciplinary collaboration on diagnosis, staging, treatment and follow up. - Includes new chapters on Cancer Metabolism and Clinical Trial Designs in Oncology and a standalone chapter on lifestyles and cancer prevention. - Features extensive updates including the latest clinical practice guidelines, decision-making algorithms, and clinical trial implications, as well as new content on precision medicine, genetics, and PET/CT imaging. - Includes revised diagnostic and treatment protocols for medical management, surgical considerations, and radiation oncology therapies, stressing a multispecialty, integrated approach to care. - Helps you find information quickly with updated indexing related to management recommendations, focused fact summaries, updated key points at the beginning of each chapter ideal for quick reference and board review, and algorithms for patient evaluation, diagnosis, and treatment options. - Offers more patient care coverage in disease chapters, plus new information on cancer as a chronic illness and cancer survivorship. - Discusses today's key topics such as immuno-oncology, functional imaging, precision medicine, the application of genetics in pathologic diagnosis and sub-categorization of tumors as well as the association of chronic infectious diseases such as HIV and cancer. - Enhanced eBook version included with purchase. Your enhanced eBook allows you to access all of the text, figures, and references from the book on a variety of devices.
Designed for the new syllabus, this book will engage and support stud ents of all abilities. Presented in vibrant full colour format with phot ographs and cartoons, Connections Maths will motivate learning and appea l to all students. Each book comes with an interactive CD-ROM with extra learning material.
The primary purpose of this book is to present information about selected topics on the interactions and applications of fuzzy + neural. Most of the discussion centers around our own research in these areas. Fuzzy + neural can mean many things: (1) approximations between fuzzy systems and neu ral nets (Chapter 4); (2) building hybrid neural nets to equal fuzzy systems (Chapter 5); (3) using neura.l nets to solve fuzzy problems (Chapter 6); (4) approximations between fuzzy neural nets and other fuzzy systems (Chap ter 8); (5) constructing hybrid fuzzy neural nets for certain fuzzy systems (Chapters 9, 10); or (6) computing with words (Chapter 11). This book is not intend to be used primarily as a text book for a course in fuzzy + neural because we have not included problems at the end of each chapter, we have omitted most proofs (given in the references), and we have given very few references. We wanted to keep the mathematical prerequisites to a minimum so all longer, involved, proofs were omitted. Elementary dif ferential calculus is the only prerequisite needed since we do mention partial derivatives once or twice.
This book is an excellent starting point for any curriculum in fuzzy systems fields such as computer science, mathematics, business/economics and engineering. It covers the basics leading to: fuzzy clustering, fuzzy pattern recognition, fuzzy database, fuzzy image processing, soft computing, fuzzy applications in operations research, fuzzy decision making, fuzzy rule based systems, fuzzy systems modeling, fuzzy mathematics. It is not a book designed for researchers - it is where you really learn the "basics" needed for any of the above-mentioned applications. It includes many figures and problem sets at the end of sections.
Welcome to the wonderful world of algebraic computation! This activity book offers puzzles, games, and activities suitable for students who want to have fun while becoming more adept in mathematical skill and ability. Algebra provides many of the core foundations for a large number of career paths. Algebra 1 Activities provides students with a practical, useful, and fun way to learn while preparing for studies in medicine, architecture, computer science, meteorology, media, statistics, accounting, engineering, industry, and parenting. Designed with both the instructor and students in mind, Algebra 1 Activities facilitates meaningful teaching and learning opportunities. It covers various mathematics topics that may be used as follow-up or supplementary activities to guided instruction at the teacher's discretion. Several activities are included for extended practice if required. They are logically arranged for a smooth progression through mastery of mathematics skills and can be adapted to fit the students' needs, abilities, and learning styles. Algebra 1 Activities allows for creativity, flexibility, and the enhancement of learning experiences in mathematics. Equip your students or yourself for the careers and challenges of the future.
An introduction to a wide range of techniques and applications used in dynamical mathematical modelling. Emphasizing algebraic concepts, the text encourages students to develop a different manner of thinking about mathematics in order to apply mathematical concepts to other fields.
This book provides an introduction to the underlying theory, fundamentals, and applications of EPR spectroscopy, as well as new developments in the area. Knowledge of the topics presented will allow the reader to interpret of a wide range of EPR spectra, as well as help them to apply EPR techniques to problem solving in a wide range of areas: organic, inorganic, biological, and analytical chemistry; chemical physics, geophysics, and minerology. Includes updated information on high frequency and multi-frequency EPR, pulsed microwave techniques and spectra analysis, dynamic effects, relaxation phenomena, computer-based spectra simulation, biomedical aspects of EPR, and more Equips readers with sufficient knowledge of EPR techniques to go on in their specialized area of interest Provides problem sets and concise bibliographies at the end of each chapter, plus several tutorial appendices on topics like mathematical operations, quantum mechanics of angular momentum, experimental considerations.
The new edition of the popular introductory textbook on numerical approximation methods and mathematical analysis, with a unique emphasis on real-world application An Introduction to Numerical Methods and Analysis helps students gain a solid understanding of a wide range of numerical approximation methods for solving problems of mathematical analysis. Designed for entry-level courses on the subject, this popular textbook maximizes teaching flexibility by first covering basic topics before gradually moving to more advanced material in each chapter and section. Throughout the text, students are provided clear and accessible guidance on a wide range of numerical methods and analysis techniques, including root-finding, numerical integration, interpolation, solution of systems of equations, and many others. This fully revised third edition contains new sections on higher-order difference methods, the bisection and inertia method for computing eigenvalues of a symmetric matrix, a completely re-written section on different methods for Poisson equations, and spectral methods for higher-dimensional problems. New problem sets—ranging in difficulty from simple computations to challenging derivations and proofs—are complemented by computer programming exercises, illustrative examples, and sample code. This acclaimed textbook: Explains how to both construct and evaluate approximations for accuracy and performance Covers both elementary concepts and tools and higher-level methods and solutions Features new and updated material reflecting new trends and applications in the field Contains an introduction to key concepts, a calculus review, an updated primer on computer arithmetic, a brief history of scientific computing, a survey of computer languages and software, and a revised literature review Includes an appendix of proofs of selected theorems and a companion website with additional exercises, application models, and supplemental resources An Introduction to Numerical Methods and Analysis, Third Edition is the perfect textbook for upper-level undergraduate students in mathematics, science, and engineering courses, as well as for courses in the social sciences, medicine, and business with numerical methods and analysis components.
Designed to engage students and lower their "fear factor", Integrative Statistics for the Social and Behavioral Sciences is a concise, user-friendly text that prepares students to use statistics in the real world. Providing depth and breadth of statistical tests, the text focuses on choosing the appropriate statistical analysis, and shows how to interpret the output and present the results.
Atkins' Physical Chemistry: Molecular Thermodynamics and Kinetics is designed for use on the second semester of a quantum-first physical chemistry course. Based on the hugely popular Atkins' Physical Chemistry, this volume approaches molecular thermodynamics with the assumption that students will have studied quantum mechanics in their first semester. The exceptional quality of previous editions has been built upon to make this new edition of Atkins' Physical Chemistry even more closely suited to the needs of both lecturers and students. Re-organised into discrete 'topics', the text is more flexible to teach from and more readable for students. Now in its eleventh edition, the text has been enhanced with additional learning features and maths support to demonstrate the absolute centrality of mathematics to physical chemistry. Increasing the digestibility of the text in this new approach, the reader is brought to a question, then the math is used to show how it can be answered and progress made. The expanded and redistributed maths support also includes new 'Chemist's toolkits' which provide students with succinct reminders of mathematical concepts and techniques right where they need them. Checklists of key concepts at the end of each topic add to the extensive learning support provided throughout the book, to reinforce the main take-home messages in each section. The coupling of the broad coverage of the subject with a structure and use of pedagogy that is even more innovative will ensure Atkins' Physical Chemistry remains the textbook of choice for studying physical chemistry.
This book defends the view that any adequate account of rational decision making must take a decision maker's beliefs about causal relations into account. The early chapters of the book introduce the non-specialist to the rudiments of expected utility theory. The major technical advance offered by the book is a 'representation theorem' that shows that both causal decision theory and its main rival, Richard Jeffrey's logic of decision, are both instances of a more general conditional decision theory. The book solves a long-standing problem for Jeffrey's theory by showing for the first time how to obtain a unique utility and probability representation for preferences and judgements of comparative likelihood. The book also contains a major new discussion of what it means to suppose that some event occurs or that some proposition is true. The most complete and robust defence of causal decision theory available.
How do you avoid the high cost of turnover and retain high-quality special education teachers in such a demanding field? Surveys show that 98% of school districts are reporting shortages of special education teachers, and that nearly a quarter of a million new special education teachers will be needed over the next few years. Special education teachers are leaving the field at twice the rate of general education teachers. Why? Special education teachers can quickly become overwhelmed by the myriad of responsibilities in their jobs-managing IEPs, alternative assessments, paraprofessionals, assistive technologies, complex legislation and paperwork, and the physical and emotional toll of such individualized instruction. Mentoring New Special Education Teachers will help administrators and other educators develop and sustain effective mentoring programs specifically designed for special education teachers, providing practical, field-tested activities and resources for both the mentors and the mentees, including such critical elements as: Effectively identifying, recruiting, and selecting mentors Action planning Evaluating progress Addressing diminishing support Dealing with burnout and isolation Vignettes of real-life mentoring experiences Figures, tables, appendices, Web sites A ready-to-use two-day workshop for training mentors Real-life vignettes and "What If" questions weave throughout the book, and trouble-shooting appendices direct you to additional Web sites and resources for further help. Mentoring New Special Education Teachers provides everything you need to effectively support and mentor your special education teachers, increase their job satisfaction, and keep your retention rates high!
Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to provide a solid foundation in statistics. It also addresses tools used by researchers to describe and summarize data ranging from single variables to assessing the relationship between variables and cause and effect among variables. The second section focuses on inferential statistics, describing how researchers draw conclusions about whole populations based on data from samples. This section also covers confidence intervals and a variety of significance tests for examining relationships between different types of variables. Additionally, tools for multivariate analyses and data interpretation are presented. Key Features: Addresses the role of statistics in evidence-based practice and program evaluation Features examples of qualitative and quantitative analysis Each chapter contains exercise problems and questions to enhance student learning Includes electronic data sets taken from actual social work arenas Offers a full ancillary digital packet including a student guide to SPSS with accompanying Data Set, an Instructor's Manual, PowerPoint slides, and a Test Bank
The goal of this book is to establish the foundation, principles, theory, and concepts that are the backbone of real, autonomous Artificial Intelligence. Presented here are some basic human intelligence concepts framed for Artificial Intelligence systems. These include concepts like Metacognition and Metamemory, along with architectural constructs for Artificial Intelligence versions of human brain functions like the prefrontal cortex. Also presented are possible hardware and software architectures that lend themselves to learning, reasoning, and self-evolution
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