Written by a prominent social work leader and trainer for social work licensing exams in the U.S., this guide is based on years of time-tested exam prep workshops conducted by the author. It mirrors the ASWB Masters’ "Knowledge, Skills, and Abilities” upon which the exam is based, as well as incorporates information from the DSM-5, which will be included in the exam starting in mid-2015. The guide is comprehensive yet focuses on the material most likely to be included on the exam, so that students can prioritize information as they study. A self-assessment section helps readers identify their strengths and weaknesses before they tackle the material. The author shares her extensive knowledge of the exam by providing useful test-taking strategies and tips for overcoming test anxiety. The 170-question practice test at the end of the guide (with explanations of the correct answers) mirrors the actual exam in both length and structure. Information covered includes human development, diversity, abuse and neglect, assessment and intervention planning, direct and indirect (micro and macro) practice, and professional values and ethics. This book will be a valuable asset for students and aspiring social workers throughout the U.S. and Canada. Key Features: Developed by a highly respected educator of social work licensure candidates Covers all the content areas on the examination, as well as new content added in 2015 Begins with a self-assessment section to help identify areas of strength and weakness Offers a wealth of test-taking tips and strategies to foster exam confidence Includes a practice test (with explanations of the correct answers) that mirrors the exam ASWB is a registered service mark of the Association of Social Work Boards, which neither sponsors nor endorses this product.

    The reader will learn to plan and manage multimedia projects, from dynamic CD-ROMs and DVDs to professional websites.

    It should be labelled 'start here'." --Pieter Jan Stappers, ID-StudioLab, Delft University of Technology

    Key concepts are combined with detailed illustrations and step-by-step exercises to acquaint readers with the building blocks of ArcGIS® Desktop including ArcMap™, for displaying and querying maps, ArcCatalog™, for organizing geographic data, and ModelBuilder™, for diagramming and processing solutions to complex spatial analysis problems. Its broad scope, simple style, and practical orientation make this book an ideal classroom text and an excellent resource for those learning GIS on their own. A data CD for working through the exercises and a fully functioning 180-day trial ArcGIS® Desktop 10 software is included.

    This guide shows that good research and lively writing do not have to be mutually exclusive.

    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.

    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.

    The text converts all programming code into the C++ language.

    It presents historical perspectives on the development of nursing theory, assessments of concept and theory development and theory evaluation, middle-range theories, and shared theories from other disciplines in the sociologic, behavioral, and biomedical sciences, focusing on the application of theory. Learning features found throughout the text include case studies and end-of-chapter summaries that help to reinforce essential concepts.

    Unlike other PR texts that steer clear of the cases, the ethical challenges, the how to counsel, and the public relations conundrums that force students to think, this book prepares students to deal with a full range of situations and arrive at effective, ethical solutions that distinguish the practice.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

    Students need to know how writers’ and speakers’ choices are shaped by elements of the rhetorical situation, including audience, occasion, and purpose. In Teaching Arguments: Rhetorical Comprehension, Critique, and Response , Jennifer Fletcher provides teachers with engaging classroom activities, writing prompts, graphic organizers, and student samples to help students at all levels read, write, listen, speak, and think rhetorically. Fletcher believes that, with appropriate scaffolding and encouragement, all students can learn a rhetorical approach to argument and gain access to rigorous academic content. Teaching Arguments opens the door and helps them pay closer attention to the acts of meaning around them, to notice persuasive strategies that might not be apparent at first glance. When we analyze and develop arguments, we have to consider more than just the printed words on the page. We have to evaluate multiple perspectives; the tension between belief and doubt; the interplay of reason, character, and emotion; the dynamics of occasion, audience, and purpose; and how our own identities shape what we read and write. Rhetoric teaches us how to do these things. Teaching Arguments will help students learn to move beyond a superficial response to texts so they can analyze and craft sophisticated, persuasive arguments—a major cornerstone for being not just college-and career-ready but ready for the challenges of the world.

    In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice.This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises.This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective.

    The new edition provides invitations - not requirements - to use technology, as well as new conceptual problems, and new projects that focus on writing and working in teams.