The Seventh Edition has been updated with stronger coverage of evidence-based practice, including content on how to read, interpret, and critique systematic reviews, which are considered by many to be a cornerstone of evidence-based practice. Also included in the Seventh Edition: a more balanced presentation of medical and social science methods and nomenclature; enhanced coverage of qualitative research; and more!

    From students with disabilities, culturally diverse students, and students with limited English proficiency to economically disadvantaged students this text provides teachers with the tools they need in their diverse classrooms. Revised to reflect the most current research, terminology and teaching practices, the strength of this text continues to be its numerous learning activities and sample lessons addressing both elementary and secondary classrooms. This edition continues its very popular multi- chapter unit on curriculum adaptations with specific strategies and activities for teaching reading, writing, and mathematics. With a new chapter on Response to Intervention and Progress Monitoring and full integration of the RTI framework, and the increase emphasis on middle and secondary students, this text continues its reign as an outstanding resource for all general education teachers. 0131381253 / 9780131381254 Teaching Students Who are Exceptional, Diverse, and at Risk in the General Education Classroom (with MyEducationLab) Package consists of 0135140870 / 9780135140871 MyEducationLab -- Access Card 0137151799 / 9780137151790 Teaching Students Who are Exceptional, Diverse, and at Risk in the General Education Classroom

    The new edition features additional styles and functions, improved font handling, and enhanced graphics capabilities. Other parts of the book have been revised to reflect user comments and suggestions. Selected sections have been rewritten to explain challenging concepts or functions, and the descriptions of both MakeIndex and BibTEX have been updated. New LATEX users will want to start with this book, and current users, particularly as they upgrade to the LATEX2e software, will be eager to obtain the most up-to-date version of its associated manual. Features Revised version of the authoritative user's guide and reference manual for the LATEX computer typesetting system. Features the new standard software release - LATEX2e. Sections rewritten to explain difficult concepts or functions.

    This book is designed to give the reader insight into the power and beauty that accrues from a rich interplay between different areas of mathematics. The book carefully develops the theory of different algebraic structures, beginning from basic definitions to some in-depth results, using numerous examples and exercises to aid the reader's understanding. In this way, readers gain an appreciation for how mathematical structures and their interplay lead to powerful results and insights in a number of different settings. * The emphasis throughout has been to motivate the introduction and development of important algebraic concepts using as many examples as possible.

    They illuminate the political, social and personal assumptions which have governed and sustained historical practice and theory. The book also brings into focus the key historiographic trends since World War Two. Key themes which are highlighted include: - The role of sources - The nation - Marxism - Radicalism - Structural history - Gender - Race - Statistics and economics Ranging widely from the earlier traditions and schools to the wake of postmodernism, authors represented include Braudel, Zeldin, Elton Carr, Hobsbawm, Joyce and Evans. This Reader provides the core reading for all History and Theory courses and will promote further debate across cognate disciplines including philosophy and literature."

    It includes even more new monographs and the latest FDA approvals. This updated edition is a book that students can count on with vital information for Peds, as well as precautions for all vulnerable populations. From pediatrics to geriatrics and from pregnancy to breast feeding considerations, "Davis's Drug Guide for Nurses" addresses the entire lifespan.

    Building on the successful top-down approach of previous editions, this fourth edition continues with an early emphasis on application-layer paradigms and application programming interfaces, encouraging a hands-on experience with protocols and networking concepts.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    Written By Two Of Today'S Most Respected Computer Science Educators, Nell Dale And John Lewis, The Text Provides A Broad Overview Of The Many Aspects Of The Discipline From A Generic View Point. Separate Program Language Chapters Are Available As Bundle Items For Those Instructors Who Would Like To Explore A Particular Programming Language With Their Students. The Many Layers Of Computing Are Thoroughly Explained Beginning With The Information Layer, Working Through The Hardware, Programming, Operating Systems, Application, And Communication Layers, And Ending With A Discussion On The Limitations Of Computing. Perfect For Introductory Computing And Computer Science Courses, Computer Science Illuminated, Third Edition's Thorough Presentation Of Computing Systems Provides Computer Science Majors With A Solid Foundation For Further Study, And Offers Non-Majors A Comprehensive And Complete Introduction To Computing.

    Aimed at undergraduate students in mathematics, physics, and engineering, the book's intuitive explanations, lack ofadvanced prerequisites, and consciously user-friendly prose style will help students to master the subject more readily than was previously possible. The key to this is the book's use of new geometric arguments in place of the standard calculational ones. These geometric arguments are communicatedwith the aid of hundreds of diagrams of a standard seldom encountered in mathematical works. A new approach to a classical topic, this work will be of interest to students in mathematics, physics, and engineering, as well as to professionals in these fields.

    He includes information on Java Platform Standard Edition 6 (Java SE 6) and offers complete coverage of the Java language, its syntax, keywords, and fundamental programming principles.

    Engineering professor Barbara Oakley knows firsthand how it feels to struggle with math. She flunked her way through high school math and science courses, before enlisting in the army immediately after graduation. When she saw how her lack of mathematical and technical savvy severely limited her options—both to rise in the military and to explore other careers—she returned to school with a newfound determination to re-tool her brain to master the very subjects that had given her so much trouble throughout her entire life. In A Mind for Numbers, Dr. Oakley lets us in on the secrets to effectively learning math and science—secrets that even dedicated and successful students wish they’d known earlier. Contrary to popular belief, math requires creative, as well as analytical, thinking. Most people think that there’s only one way to do a problem, when in actuality, there are often a number of different solutions—you just need the creativity to see them. For example, there are more than three hundred different known proofs of the Pythagorean Theorem. In short, studying a problem in a laser-focused way until you reach a solution is not an effective way to learn math. Rather, it involves taking the time to step away from a problem and allow the more relaxed and creative part of the brain to take over. A Mind for Numbers shows us that we all have what it takes to excel in math, and learning it is not as painful as some might think!

    Integrated central case studies woven throughout each chapter, use real-life stories to give you a tangible and engaging framework around which to learn and understand the science behind environmental issues. Printed on FSC (Forest Stewardship Council) certified paper, the newly revised Fourth Edition engages you through the addition of new EnvisionIt photo essays.

    Packed with full-color illustrations and case studies, this new edition offers a cutting-edge presentation of criminalistics and related laboratory subjects, including new chapters on forensic nursing and forensic entomology/botany. Written by highly respected experts, the book covers the very latest theories and practices in areas such as DNA testing, crime reconstruction, toxicology, chemistry of explosives and arson, and vehicle reconstruction. Also included are an instructor's manual and laboratory exercise manual.

    Non- mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages. Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development. He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D. His scholarly work centers on the application and development of statistical methodology and learning algorithms. Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. Addressing practical concerns extends beyond model fitting to topics such as handling class imbalance, selecting predictors, and pinpointing causes of poor model performance-all of which are problems that occur frequently in practice. The text illustrates all parts of the modeling process through many hands-on, real-life examples. And every chapter contains extensive R code f