Most students worry about what an admissions officer looks for in a writing sample. But that’s the wrong way to approach this vital component, says former college admissions officer Harry Bauld. At Brown and Columbia, he saw what prospective students often did wrong—and now tells you how to do it right.On Writing the College Application Essay is his inside guide to writing a college application essay that will stand out from the pack. Baum advises you on how to avoid platitudes and find your authentic voice, gives you tools and ideas that will spark your imagination, and shows you how to approach themes with originality and panache to make even the most tired topics—the ones most students should stay away from—fresh, such as:The trip (“I had to adjust to a whole new way of life.”)My favorite things (puppy dogs, freedom, and chocolate chip cookies)The pageant contestant (“I think World Peace is the most important issue facing us today.”)The jock (“Through wrestling I have learned to set goals and to work with people.”)The autobiography (“Hello, my name is . . . ”)Tales of my success (“But, finally, when I crossed the finish line . . . ”)Pet death (“As I watched Buttons’s life ebb away, I came to value . . . ”)Getting into the college of your dreams is tough. The competition is fierce. For more than twenty-five years, On Writing the College Application Essay has helped thousands of students improve their chances. Now, let it work for you.

    With richly evocative classroom vignettes provided by practicing teachers, as well as the most case studies - three per chapter - of any Introductory text, Santrock's Educational Psychology helps students think critically about the research basis for best practices. Additionally, Santrock's hallmark Learning System organizes the content into manageable chunks to support retention and mastery, and makes it much more likely that students will have an engaging and successful course experience.

    Terms are introduced in the context of human anatomy and physiology to help you understand exactly what they mean, and case studies and vignettes throughout the book demonstrate how they're used in practice. With all this plus NEW animations and games on the companion CD, you'll be amazed at how easily medical terminology becomes part of your vocabulary.

    This edition contains NEW tables on Properties of Ionic Liquids, Solubilities of Hydrocarbons in Sea Water, Solubility of Organic Compounds in Superheated Water, and Nutritive Value of Foods. It also updates many tables including Critical Constants, Heats of Vaporization, Aqueous Solubility of Organic Compounds, Vapor Pressure of Mercury, Scientific Abbreviations and Symbols, and Bond Dissociation Energies. The 88th Edition also presents a new Foreword written by Dr. Harold Kroto, a 1996 Nobel Laureate in Chemistry.

    Now available with a personalized online learning plan, this social work-specific book looks at lifespan through the lens of social work theory and practice. The authors use an empowerment approach to cover human development and behavior theories within the context of family, organizational, and community systems. Using a chronological lifespan approach, the authors present separate chapters on biological, psychological, and social impacts at the different lifespan stages with an emphasis on strengths and empowerment.

    Excellent Board review.

    This book provides an introduction to the field of solid state physics for undergraduate students in physics, chemistry, engineering, and materials science.

    With expanded coverage of ethics, analysis processes, and approaches, authors Catherine Marshall and Gretchen B. Rossman, have updated this highly popular text to reflect the advances and challenges presented by provocative developments and new applications since the previous edition.

    An interesting and reader friendly writing style makes for a clear presentation, complete with all the necessary assumptions and mathematical details. Chapter topics include probability concepts and applications, decision models and decision trees, regression models, forecasting, inventory control models, linear programming modeling applications and computer analyses, network models, project management, simulation modeling, and more. For an introduction toquantitative analysis, quantitative management, operations research, or management science-especially for those individuals preparing for work in agricultural economics and health care fields.

    With this Ninth Edition, the Number One best-selling non-majors microbiology text extends its trusted and reliable approach with improved disease chapters that feature efficient new Disease in Focus boxes, a thoroughly revised immunity chapter (17), new options for the Microbiology Place website/CD-Rom, and a new Media Manager instructor presentation package with 30 multi-step animations.

    These sections together make an appropriate one-term advanced/graduate level course (mathematical prerequisites: vector analysis and simple partial-differential equations). The book is printed to make it easy for readers to identify these sections.• The remaining Track 2 material provides a wealth of advanced topics instructors can draw from to flesh out a two-term course, with Track 1 sections serving as prerequisites.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    Includes new and extended problem sets in every chapter, all of which have been annotated for level and skill type Features three new chapters on advanced topics including vP shells, object shells, control, gapping and ellipsis and an additional chapter on advanced topics in binding Offers a brief survey of both Lexical-Functional Grammar and Head-Driven Phrase Structure Grammar Succeeds in strengthening the reader's foundational knowledge, and prepares them for more advanced study Supported by an instructor's manual and online resources for students and instructors, available at www.blackwellpublishing.com/carnie

    Using graphics, checklists, and sample forms, this guide readies you for each step of the process, including selecting the committee, getting acclimated to academic writing, preparing for your oral defense, and publishing your research. New features include:A chapter on ethical considerations Expanded coverage of digital data collection and the Internet More detailed information on conducting the literature review A discussion of how to develop a theoretical or conceptual framework

    Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, recognize faces or spoken speech, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. "Introduction to Machine Learning" is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. It discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the student can easily move from the equations in the book to a computer program. The book can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are concerned with the application of machine learning methods.After an introduction that defines machine learning and gives examples of machine learning applications, the book covers supervised learning, Bayesian decision theory, parametric methods, multivariate methods, dimensionality reduction, clustering, nonparametric methods, decision trees, linear discrimination, multilayer perceptrons, local models, hidden Markov models, assessing and comparing classification algorithms, combining multiple learners, and reinforcement learning.