Emphasizing the importance of the research process, the book shows students how social scientists design research studies, introduces the variety of observation modes used by sociologists, and covers the "how-to's" and "whys" of social research methods. Students learn how to conduct various types of research, when it is appropriate to use each method, and how to analyze qualitative and quantitative data. The 11th edition provides students with the necessary tools for understanding social research methods and for applying these concepts both inside and outside the classroom--as researchers and as consumers of research.

      An exceptional pedagogical package that ties the textbook to online MyDevelopmentLab study tools complements the student-centered approach of the book and offers students the benefit of frequent self-assessment.

    The authors' six-step model clearly illustrates and elucidates the process of dealing with people in crisis: Defining the Problem, Ensuring Client Safety, Providing Support, Examining Alternatives, Making Plans, and Obtaining Commitment. Using this model, the authors then build specific strategies for handling a myriad of different crisis situations, accompanied in many cases with the dialogue that a practitioner might use when working with the individual in crisis. New videos, available through a DVD and through CourseMate (both of which are available for purchase with the text), correlate with the text and demonstrate crisis intervention techniques, ensuring that you not only understand the theoretical underpinnings of crisis intervention theories, but also know how to apply them in crisis situations.

    The first abnormal psychology book to present a thoroughly integrated multicultural perspective--based on the authors' view that cross-cultural comparisons can greatly enhance the understanding of disorders--the text provides extensive coverage and integration of multicultural models, explanations, and concepts. The book also helps you gain an understanding of abnormal behavior as scientific and clinical endeavors, while providing insight into the tools that mental health professionals use to study and treat disorders.

    A new foreword by Kip Thorne, the current Richard Feynman Professor of Theoretical Physics at Caltech, discusses the relevance of the new edition to today's readers. This boxed set also includes Feynman's new Tips on Physics—the four previously unpublished lectures that Feynman gave to students preparing for exams at the end of his course. Thus, this 4-volume set is the complete and definitive edition of The Feynman Lectures on Physics. Packaged in a specially designed slipcase, this 4-volume set provides the ultimate legacy of Feynman's extraordinary contribution to students, teachers, researches, and lay readers around the world.

    It is possible to develop significant skills in order to make the writing process much easier than you think. In "Research Strategies," author William Badke offers a clear, simple, and often humorous roadmap for conducting research and navigating the vast new world of information and technology. In this, the fourth edition, Badke details the entire research paper process from start to finish. "Research Strategies" provides a plethora of insightful and helpful information, including:Finding and narrowing a topic Creating an outline Searching databases Understanding metadata Using library catalogs and journal databases Conducting Internet research Organizing research notes Writing the actual paper"Research Strategies" explains the skills and strategies you need to efficiently and effectively complete a research project from topic to finished product. With the information provided here, research doesn't have to be frustrating or boring. Badke's strategies present a sure path through the amazing and complex new world of information.

    It offers superior coverage of all key areas, including descriptive chemistry, MO theory, bonding, and physical inorganic chemistry. Chapter topics are presented in logical order and include: basic concepts; nuclear properties; an introduction to molecular symmetry; bonding in polyatomic molecules; structures and energetics of metallic and ionic solids; acids, bases, and ions in aqueous solution; reduction and oxidation; non-aqueous media; and hydrogen. Four special topic chapters, chosen for their currency and interest, conclude the book. For researchers seeking the latest information in the field of inorganic chemistry.

    It provides a simple, thorough survey of elementary topics, starting with set theory and advancing to metric and topological spaces, connectedness, and compactness. 1975 edition.

    R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. * Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. * Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. * The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. * Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. * Includes numerous worked examples and exercises within each chapter. * Accompanied by a website featuring worked examples, data sets, exercises and solutions: http: //www.imperial.ac.uk/bio/research/crawl... Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

    The authors review their earlier findings and then synthesize what has been learned since 1990 about college's influences on students' learning. The book also discusses the implications of the findings for research, practice, and public policy. This authoritative and comprehensive analysis of the literature on college-impact is required reading for anyone interested in higher education practice, policy, and promise3/4faculty, administrators, researchers, policy analysts, and decision-makers at every level.

    It provides clear, simple explanations and concrete examples of complex concepts, making a wide variety of commonly used critical theories accessible to novices without sacrificing any theoretical rigor or thoroughness.This new edition provides in-depth coverage of the most common approaches to literary analysis today: feminism, psychoanalysis, Marxism, reader-response theory, new criticism, structuralism and semiotics, deconstruction, new historicism, cultural criticism, lesbian/gay/queer theory, African American criticism, and postcolonial criticism. The chapters provide an extended explanation of each theory, using examples from everyday life, popular culture, and literary texts; a list of specific questions critics who use that theory ask about literary texts; an interpretation of F. Scott Fitzgerald's The Great Gatsby through the lens of each theory; a list of questions for further practice to guide readers in applying each theory to different literary works; and a bibliography of primary and secondary works for further reading.

    The text begins with a discussion of the real number system as a complete ordered field. (Dedekind's construction is now treated in an appendix to Chapter I.) The topological background needed for the development of convergence, continuity, differentiation and integration is provided in Chapter 2. There is a new section on the gamma function, and many new and interesting exercises are included. This text is part of the Walter Rudin Student Series in Advanced Mathematics.

    Beginning with the background and very nature of probability theory, the book then proceeds through sample spaces, combinatorial analysis, fluctuations in coin tossing and random walks, the combination of events, types of distributions, Markov chains, stochastic processes, and more. The book's comprehensive approach provides a complete view of theory along with enlightening examples along the way.

    But that does not even begin to convey what the Berger experience is: What makes these bestselling textbooks so distinctive is the unmistakable presence of KATHLEEN STASSEN BERGER on every page, in writing that continually draws on the author’s teaching and family life to demonstrate a remarkable understanding not just of the field, but of students’ questions, their concerns, and their lives.The distinctive, definitive BERGER touch is evident throughout her new textbook, Invitation to the Life Span. This brief, original, 15-chapter textbook was created from page 1 to address the challenges teachers and students face when covering the entire life span in a semester (or even a quarter!). The hallmark Berger qualities are all here—the relatable presentation of research, the inclusive approach to world cultures, the study help that builds critical thinking and observational skills, the outstanding media and supplements—and all held together with Berger’s skill in bringing students and the science together.

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.