{"title":"Mathematics","description":"\u003cp\u003eCollege math textbooks from algebra and calculus through advanced analysis — authentic US editions with verified ISBNs and free US shipping.\u003c\/p\u003e","products":[{"product_id":"latent-variable-modeling-using-r-a-step-by-step-guide","title":"Latent Variable Modeling Using R A Step by Step Guide by A. Alexander Beaujean","description":"\u003cp\u003eThis step-by-step guide is written for \u003cb\u003eR\u003c\/b\u003e and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the \u003ci\u003elavaan\u003c\/i\u003e package, this book is designed to help readers quickly understand LVMs and their analysis in \u003cb\u003eR\u003c\/b\u003e. The author reviews the reasoning behind the syntax selected and provides examples that demonstrate how to analyze data for a variety of LVMs.　 Featuring examples applicable to psychology, education, business, and other social and health sciences, minimal text is devoted to theoretical underpinnings. The material is presented without　the use of matrix algebra. As a whole the book prepares readers to write about and interpret LVM results they obtain in \u003cb\u003eR\u003c\/b\u003e.\u003c\/p\u003e \u003cp\u003eEach chapter features background information, boldfaced key　 terms defined in the glossary, detailed interpretations of \u003cb\u003eR\u003c\/b\u003e output, descriptions of how to write the analysis of results for publication, a summary, \u003cb\u003eR\u003c\/b\u003e based practice exercises (with solutions included in the back of the book), and references and related readings. Margin notes help readers better understand LVMs and write their own \u003cb\u003eR\u003c\/b\u003e syntax. Examples using data from published work across a variety of disciplines demonstrate how to use \u003cb\u003eR\u003c\/b\u003e syntax for analyzing and interpreting results. \u003cb\u003eR\u003c\/b\u003e functions, syntax, and the corresponding results appear in gray boxes to help readers quickly locate this material. A unique index helps readers quickly locate R\u003cb\u003e　\u003c\/b\u003efunctions, packages, and datasets. The book and accompanying website at http:\/\/blogs.baylor.edu\/rlatentvariable\/ provides all of the data for the book's examples and exercises as well as \u003cb\u003eR\u003c\/b\u003e syntax so readers can replicate the analyses. The book reviews how to enter the data into \u003cb\u003eR\u003c\/b\u003e, specify the LVMs, and obtain and interpret the estimated parameter values.\u003c\/p\u003e \u003cp\u003eThe book opens with the fundamentals of using \u003cb\u003eR\u003c\/b\u003e including how to download the program, use functions, and enter and manipulate data. Chapters 2 and 3 introduce and then extend path models to include latent variables. Chapter 4 shows readers how to analyze a latent variable model with data from more than one group, while Chapter 5 shows how to analyze a latent variable model with data from more than one time period. Chapter 6 demonstrates the analysis of dichotomous variables, while Chapter 7 demonstrates how to analyze LVMs with missing data. Chapter 8 focuses on sample size determination using Monte Carlo methods, which can be used with a wide range of statistical models and account for missing data. The final chapter examines hierarchical LVMs, demonstrating both higher-order and bi-factor approaches. The book concludes with three Appendices: a review of common measures of model fit including their formulae and interpretation; syntax for other \u003cb\u003eR\u003c\/b\u003e latent variable models packages; and solutions for each chapter's exercises.\u003c\/p\u003e \u003cp\u003eIntended as a supplementary text for graduate and\/or advanced undergraduate courses on latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, business, economics, and social and health sciences, this book also appeals to researchers in these fields. Prerequisites include familiarity with basic statistical concepts, but knowledge of \u003cb\u003eR\u003c\/b\u003e is \u003ci\u003enot\u003c\/i\u003e assumed.\u003c\/p\u003e","brand":"Routledge","offers":[{"title":"Default Title","offer_id":45661228630206,"sku":null,"price":61.19,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0536\/0592\/5054\/files\/5911603482846.jpg?v=1765181782"},{"product_id":"mathematical-analysis-i","title":"Mathematical Analysis I by V. A. Zorich","description":"\u003cp\u003eThis second edition of a very popular two-volume work presents a thorough first course in analysis, leading from real numbers to such advanced topics as differential forms on manifolds; asymptotic methods; Fourier, Laplace, and Legendre transforms; elliptic functions; and distributions. Especially notable in this course are the clearly expressed orientation toward the natural sciences and the informal exploration of the essence and the roots of the basic concepts and theorems of calculus. Clarity of exposition is matched by a wealth of instructive exercises, problems, and fresh applications to areas seldom touched on in textbooks on real analysis.\u003c\/p\u003e \u003cp\u003eThe main difference between the second and first editions is the addition of a series of appendices to each volume. There are six of them in the first volume and five in the second. The subjects of these appendices are diverse. They are meant to be useful to both students (in mathematics and physics) and teachers, who may be motivated by different goals. Some of the appendices are surveys, both prospective and retrospective. The final survey establishes important conceptual connections between analysis and other parts of mathematics.\u003c\/p\u003e \u003cp\u003eThe first volume constitutes a complete course in one-variable calculus along with the multivariable differential calculus elucidated in an up-to-date, clear manner, with a pleasant geometric and natural sciences flavor.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e","brand":"Springer Berlin Heidelberg","offers":[{"title":"Default Title","offer_id":45661241901246,"sku":null,"price":38.24,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0536\/0592\/5054\/files\/100393483492.jpg?v=1765181807"},{"product_id":"enterprise-architecture-at-work-modelling-communication-and-analysis","title":"Enterprise Architecture at Work Modelling, Communication and Analysis by Marc Lankhorst","description":"\u003cp\u003eLankhorst and his co‐authors present ArchiMate® 3.0, enterprise modelling language that captures the complexity of architectural domains and their relations and allows the construction of integrated enterprise architecture models. They provide architects with concrete instruments that improve their architectural practice. As this is not enough, they additionally present techniques and heuristics for communicating with all relevant stakeholders about these architectures. Since an architecture model is useful not only for providing insight into the current or future situation but can also be used to evaluate the transition from ‘as‐is’ to ‘to‐be’, the authors also describe analysis methods for assessing both the qualitative impact of changes to an architecture and the quantitative aspects of architectures, such as performance and cost issues.\u003c\/p\u003e\u003cp\u003eThe modelling language presented has been proven in practice in many real‐life case studies and has been adopted by The Open Group as an international standard. 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The book aims at providing the reader with a deep understanding of the structural properties of graphs that are useful for the design of efficient algorithms. These algorithms have applications in finite state machine modelling, social network theory, biology, and mathematics. The book contains many exercises, some up at present-day research-level. The exercises encourage the reader to discover new techniques by putting things in a clear perspective. A study of this book will provide the reader with many powerful tools to model and tackle problems in real-world scenarios.","brand":"Springer Nature Singapore","offers":[{"title":"Default Title","offer_id":45661242065086,"sku":null,"price":42.07,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0536\/0592\/5054\/files\/12062003485681.jpg?v=1765181808"},{"product_id":"geometry-of-deep-learning-a-signal-processing-perspective","title":"Geometry of Deep Learning A Signal Processing Perspective by Jong Chul Ye","description":"\u003cp\u003eThe focus of this book is on providing students with insights into geometry that can help them understand deep learning from a unified perspective. Rather than describing deep learning as an implementation technique, as is usually the case in many existing deep learning books, here, deep learning is explained as an ultimate form of signal processing techniques that can be imagined. \u003c\/p\u003e\u003cp\u003eTo support this claim, an overview of classical kernel machine learning approaches is presented, and their advantages and limitations are explained. Following a detailed explanation of the basic building blocks of deep neural networks from a biological and algorithmic point of view, the latest tools such as attention, normalization, Transformer, BERT, GPT-3, and others are described. Here, too, the focus is on the fact that in these heuristic approaches, there is an important, beautiful geometric structure behind the intuition that enables a systematic understanding. A unified geometric analysis to understand the working mechanism of deep learning from high-dimensional geometry is offered. Then, different forms of generative models like GAN, VAE, normalizing flows, optimal transport, and so on are described from a unified geometric perspective, showing that they actually come from statistical distance-minimization problems.\u003c\/p\u003e\u003cp\u003eBecause this book contains up-to-date information from both a practical and theoretical point of view, it can be used as an advanced deep learning textbook in universities or as a reference source for researchers interested in acquiring the latest deep learning algorithms and their underlying principles. 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The book teaches \"Matlab-style\" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.\u003c\/p\u003e\u003cp\u003e\u003ci\u003eFrom the reviews: \u003c\/i\u003eLangtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eF. H. Wild III, Choice, Vol. 47 (8), April 2010\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eThose of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” \u003cbr\u003e\u003c\/i\u003e\u003cb\u003eJohn D. Cook, The Mathematical Association of America, September 2011\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eThis book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science.\u003cbr\u003e\u003c\/i\u003e\u003cb\u003eAlex Small, IEEE, CiSE Vol. 14 (2), March\u003c\/b\u003e\u003cb\u003e \u003c\/b\u003e\u003cb\u003e\/April 2012 \u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e“This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” \u003cbr\u003e\u003cb\u003eJoan Horvath, Computing Reviews, March 2015 \u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e","brand":"Springer Berlin Heidelberg","offers":[{"title":"Default Title","offer_id":45661242261694,"sku":null,"price":62.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0536\/0592\/5054\/files\/209983483492.jpg?v=1765181811"},{"product_id":"introduction-to-statistics-and-data-analysis","title":"Introduction to Statistics and Data Analysis by Roxy Peck","description":"Peck and Olsen's INTRODUCTION TO STATISTICS AND DATA ANALYSIS, 7th Edition helps you develop the ability to think statistically through its focus on conceptual understanding, use of real data and interpretation and communication of statistical information. 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WebAssign grants access to the ebook, assessments and analytics to enable you to be a self-sufficient learner and help you succeed in your course.","brand":"Cengage Learning","offers":[{"title":"Default Title","offer_id":45661242294462,"sku":null,"price":162.56,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0536\/0592\/5054\/files\/2743413488673.jpg?v=1765181812"},{"product_id":"proofs-from-the-book","title":"Proofs from THE BOOK by Martin Aigner","description":"\u003cp\u003eThis revised and enlarged sixth edition of \u003ci\u003eProofs from THE BOOK\u003c\/i\u003e features an entirely new chapter on Van der Waerden’s permanent conjecture, as well as additional, highly original and delightful proofs in other chapters.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFrom the citation on the occasion of the 2018 \"Steele Prize for Mathematical Exposition\"\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e \u003ci\u003e“... It is almost impossible to write a mathematics book that can be read and enjoyed by people of all levels and backgrounds, yet Aigner and Ziegler accomplish this feat of exposition with virtuoso style. [...] This book does an invaluable service to mathematics, by illustrating for non-mathematicians what it is that mathematicians mean when they speak about beauty.”\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFrom the Reviews\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003e\"... Inside PFTB (Proofs from The Book) is indeed a glimpse of mathematical heaven, where clever insights and beautiful ideas combine in astonishing and glorious ways. There is vast wealth within its pages, one gem after another. ... Aigner and Ziegler... write: \"... all we offer is the examples that we have selected, hoping that our readers will share our enthusiasm about brilliant ideas, clever insights and wonderful observations.\" I do. ... \"\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003eNotices of the AMS, August 1999\u003c\/p\u003e\u003cp\u003e\u003ci\u003e\"... This book is a pleasure to hold and to look at: ample margins, nice photos, instructive pictures and beautiful drawings ... It is a pleasure to read as well: the style is clear and entertaining, the level is close to elementary, the necessary background is given separately and the proofs are brilliant. ...\"\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003eLMS Newsletter, January 1999\u003c\/p\u003e\u003cp\u003e\u003ci\u003e\"Martin Aigner and Günter Ziegler succeeded admirably in putting together a broad collection of theorems and their proofs that would undoubtedly be in the Book of Erdös. 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The book also covers basic data structures and sorting algorithms, which is a nice bonus. ... every 1 – pager has a simple picture, making it easy to remember. This is a great way to learn how to identify hundreds of problem types.\" (Steve Yegge, Get that Job at Google)\u003c\/p\u003e\u003cp\u003e\"Steven Skiena’s Algorithm Design Manual retains its title as the best and most comprehensive practical algorithm guide to help identify and solve problems. ... Every programmer should read this book, and anyone working in the field should keep it close to hand. ... This is the best investment ... a programmer or aspiring programmer can make.\" (Harold Thimbleby, Times Higher Education)\u003c\/p\u003e\u003cp\u003e\"It is wonderful to open to a random spot and discover aninteresting algorithm. This is the only textbook I felt compelled to bring with me out of my student days.... 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