This brief edition of the most widely adopted book of its kind offers all of the editorial features of the longer book with about half the stories and writer commentaries in a shorter, less expensive format.

    Drugs, Behavior, and Modern Society, 6/e, examines the impact of drug-taking behavior on our society and our daily lives.  The use and abuse of a wide range of licit and illicit drugs are discussed from historical, biological, psychological, and sociological perspectives.  The use of Drugs in our lives and drug-taking behavior, legally restricted drugs in our society, legal drugs in our society, medicinal drugs, treatment, prevention, and education.  Forstudents, or people working with drug related topics in the fields of psychology and health.

    Problem solving and mathematical modeling are introduced early and reinforced throughout, so that when students finish the course, they have a solid foundation in the principles of mathematical thinking. This comprehensive, evenly paced book provides complete coverage of the function concept and integrates substantial graphing calculator materials that help students develop insight into mathematical ideas. The authors' attention to detail and clarity, as in James Stewart's market-leading Calculus text, is what makes this text the market leader.

    Born in the mid-1990s to the mid-2000s and later, iGen is the first generation to spend their entire adolescence in the age of the smartphone. With social media and texting replacing other activities, iGen spends less time with their friends in person—perhaps why they are experiencing unprecedented levels of anxiety, depression, and loneliness. But technology is not the only thing that makes iGen distinct from every generation before them; they are also different in how they spend their time, how they behave, and in their attitudes toward religion, sexuality, and politics. They socialize in completely new ways, reject once sacred social taboos, and want different things from their lives and careers. More than previous generations, they are obsessed with safety, focused on tolerance, and have no patience for inequality. iGen is also growing up more slowly than previous generations: eighteen-year-olds look and act like fifteen-year-olds used to. As this new group of young people grows into adulthood, we all need to understand them: Friends and family need to look out for them; businesses must figure out how to recruit them and sell to them; colleges and universities must know how to educate and guide them. And members of iGen also need to understand themselves as they communicate with their elders and explain their views to their older peers. Because where iGen goes, so goes our nation—and the world.

    Topics include: Limits, Derivatives, and Integrations.

    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

    Psychology of Learning for Instruction, Third Edition, focuses on the applications and implications of the learning theories. Using excellent examples ranging from primary school instruction to corporate training, this text combines the latest thinking and research to give readers the opportunity to explore the individual theories as viewed by the experts. Readers are encouraged to apply "reflective practice," which is designed to foster a critical and reflective mode of thinking when considering any particular approach to learning and instruction. Provides readers with the practical knowledge needed to apply learning theories to instruction. KEY TOPICS: This text addresses learning as it relates to behavior, cognition, development, biology, motivation and instruction. MARKET: Pre-service and in-service teachers, and educational psychologists.

    Formulating the principles of dialectical materialism, they believed that labor creates wealth, hence capitalism is exploitive and antithetical to freedom.This new edition includes an extensive introduction by Gareth Stedman Jones, Britain's leading expert on Marx and Marxism, providing a complete course for students of The Communist Manifesto, and demonstrating not only the historical importance of the text, but also its place in the world today.For more than seventy years, Penguin has been the leading publisher of classic literature in the English-speaking world. With more than 1,700 titles, Penguin Classics represents a global bookshelf of the best works throughout history and across genres and disciplines. Readers trust the series to provide authoritative texts enhanced by introductions and notes by distinguished scholars and contemporary authors, as well as up-to-date translations by award-winning translators.

    Several of the data display strategies from previous editions are now presented in re-envisioned and reorganized formats to enhance reader accessibility and comprehension. The Third Edition's presentation of the fundamentals of research design and data management is followed by five distinct methods of analysis: exploring, describing, ordering, explaining, and predicting. Miles and Huberman′s original research studies are profiled and accompanied with new examples from Salda�a′s recent qualitative work. The book′s most celebrated chapter, Drawing and Verifying Conclusions, is retained and revised, and the chapter on report writing has been greatly expanded, and is now called Writing About Qualitative Research. Comprehensive and authoritative, Qualitative Data Analysis has been elegantly revised for a new generation of qualitative researchers.

    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

    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.

    The best-selling Mastering the World of Psychology speaks to students in a direct and accessible manner. The author's voice and writing style, combined with a strong pedagogical framework, support students of diverse backgrounds and educational needs. The book relates essential key concepts in a way that is meaningful to students' lives and careers. No introductory psychology textbook does more to help students get better grades than Mastering the World of Psychology.

    Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work.Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization.

    Fully updated and revised to deal with recent changes to the GMAT, they were designed with a content-based approach.The Critical Reasoning Guide demystifies critical reasoning by teaching a clear, consistent, and effective approach to understanding an argument’s logic and choosing the best answer to the given question. Unlike other guides that attempt to convey everything in a single tome, the Critical Reasoning Strategy Guide is designed to provide deep, focused coverage of one specialized area tested on the GMAT. As a result, students benefit from thorough and comprehensive subject material, clear explanations of fundamental principles, and step-by-step instructions of important techniques. In-action practice problems and detailed answer explanations challenge the student, while topical sets of Official Guide problems provide the opportunity for further growth. Used by itself or with other Manhattan GMAT Strategy Guides, the Critical Reasoning Guide will help students develop all the knowledge, skills, and strategic thinking necessary for success on the GMAT. Purchase of this book includes one year of access to Manhattan GMAT’s online computer-adaptive practice exams and Critical Reasoning Question Bank. All of Manhattan Prep’s GMAT Strategy Guides are aligned with both the 2015 Edition and 13th Edition GMAC Official Guide.

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.