Beginning with an introduction to the diagnostic interview, the Pocket Guide addresses the goals of the interview, provides an efficient structure for learning how to conduct one, reviews the screening questions, and then tackles the ways in which DSM-5T, with its updated approaches to diagnosis and classification, impacts the interview going forward. Significant revisions from DSM-IV-TRr to DSM-5T are reviewed. The final chapter, the core of the guide, walks the reader through a complete diagnostic exam that includes the follow-up questions for each of the DSM-5T disorder classes. The book is useful for beginners learning the format and flow of the diagnostic interview and for seasoned clinicians conducting an interview consistent with the significant revisions reflected in DSM-5T. Not intended to replace DSM-5T itself or psychiatric interview texts, The Pocket Guide to the DSM-5T Diagnostic Exam is a pragmatic and concise resource for diagnosing a person in mental distress while establishing a therapeutic relationship.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    Readers learn why theory matters in designing and implementing high-quality instruction; how to critically evaluate the assumptions and beliefs that guide their own work with students; and the benefits of approaching everyday teaching situations from multiple theoretical perspectives. Every chapter features classroom application activities and illuminating teaching vignettes. Of particular utility to graduate students, the book also addresses research applications, including descriptions of exemplary studies informed by each theoretical model.

    Each technique is introduced with a simple, jargon-free explanation, practical examples, and hands-on guidance for solving real problems with Excel or a TI-83/84 series calculator, including Plus models. Hate math? No sweat. You'll be amazed how little you need! For those who do have an interest in mathematics, optional "Equation Blackboard" sections review the equations that provide the foundations for important concepts. David M. Levine is a much-honored innovator in statistics education. He is Professor Emeritus of Statistics and Computer Information Systems at Bernard M. Baruch College (CUNY), and co-author of several best-selling books, including Statistics for Managers using Microsoft Excel, Basic Business Statistics, Quality Management, and Six Sigma for Green Belts and Champions. Instructional designer David F. Stephan pioneered the classroom use of personal computers, and is a leader in making Excel more accessible to statistics students. He has co-authored several textbooks with David M. Levine. Here's just some of what you'll learn how to do... Use statistics in your everyday work or study Perform common statistical tasks using a Texas Instruments statistical calculator or Microsoft Excel Build and interpret statistical charts and tables "Test Yourself" at the end of each chapter to review the concepts and methods that you learned in the chapter Work with mean, median, mode, standard deviation, Z scores, skewness, and other descriptive statistics Use probability and probability distributions Work with sampling distributions and confidence intervals Test hypotheses and decision-making risks with Z, t, Chi-Square, ANOVA, and other techniques Perform regression analysis and modeling The easy, practical introduction to statistics--for everyone! Thought you couldn't learn statistics? Think again. You can--and you will!

    Following on the success of the first six editions of the series, this work introduces theoretical and pedagogical innovations in statics, dynamics, and mechanics of materials education.

    This volume also features increased coverage of computational modelling, discussions of prominent methodological advances and an enhanced art programme.

    Intended for students of General Chemistry, this text contains: macroscopic to microscopic molecular illustrations; step-by-step worked exercises in every chapter; and a range of end-of-chapter problems, which provide applications covering a variety of freshman interests, including engineering, medicine, materials, and environmental studies.

    This new and expanded third edition continues to offer students and readers the best one-volume introduction to the field.The bewildering variety of approaches, theorists and technical language is lucidly and expertly unraveled. Unlike many books which assume certain positions about the critics and the theories they represent, Peter Barry allows readers to develop their own ideas once first principles and concepts have been grasped.

    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.

    New chapters cover criminal behavior theories and psychological profiling; autoerotic deaths, and occult crimes, plus two new chapters detailing infamous unsolved crimes/criminals: Jack the Ripper and the Jon Benet Ramsey case. The authors′ continuing research and activities in the field result in a multitude of new case studies for this book, often included as boxed inserts.

    Written specifically for students with no previous experience of research and research methodology, the writing style is simple and clear and the author presents this complex subject in a straightforward way that empowers readers to tackle research with confidence. The book has been revised and updated to include extended coverage of qualitative research methods in addition to existing comprehensive coverage of quantitative methods. There are also brand new learning features such as reflective questions throughout the text to help students consolidate their knowledge.

    This book includes a companion CD-ROM that adds a visual emphasis with animations.

    Encompassing recent advances in molecular pharmacology and brain imaging, Drugs, The Brain and Behavior offers a unique breadth of coverage from historical accounts of drug use, through clinical and preclinical behavioural studies, to the latest research on drug effects in transgenic mouse models.

    It demonstrates to students how the concepts and theories of deviance can be applied to the world around them. The authors include both theoretical analyses and ethnographic illustrations of how deviance is socially constructed, organized, and managed. The Adlers challenge the reader to see the diversity and pervasiveness of deviance in society by covering a wide variety of deviant acts represented throughout the text. Most importantly, the Adlers present deviance as a component of society and examine the construction of deviance in terms of differential social power, whereby some members of society have the power to define other whole groups as "deviant." The book takes an "interactionist" or "constructionist" perspective on deviance, looking at the processes in society that create deviance. The authors have selected studies that are ethnographic in character, focusing on the experiences of deviants, the deviant-making process, and the ways in which people who are labeled as deviant in society react to that label.

    The revised structure, separating out the introductory and more advanced material will make it easier to use the book on a variety of courses. This new edition now includes chapters on Interaction Design, Universal Access and Rich Interaction, as well as covering the latest developments in ubiquitous computing and Web technologies, making it the ideal text to provide a grounding in HCI theory and practice.