In this book, a wealth of exercises are provided throughout each section, designed to reinforce learning and the logical comprehension of topics. The use of real data is incorporated much more extensively than in any other book on the market. Consist of strong coverage of computer-based methods, especially in the coverage of analysis of variance and regression. This text stresses mastery of methods most often used in medical research, with specific reference to actual medical literature and actual medical research. The approach minimizes mathematical formulation, yet gives complete explanations of all important concepts. Every new concept is systematically developed through completely worked-out examples from current medical research problems. Computer output is used to illustrate concepts when appropriate.

    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

    It has become known for its engaging writing style, instructional art program and focus on active learning. We are so excited to offer a robust learning program with student-focused learning activities, allowing the student to manage their learning while you easily manage their assessment. Detailed reports show how your assignments measure various learning objectives from the book (or input your own!), levels of Bloom's Taxonomy or other categories, and how your students are doing. The Cowan Learning program will save you time and improve your student's success in this course.

    Introducing students to the many facets of neural networks, this text provides many case studies to illustrate their real-life, practical applications.

    To reach this unique audience, Whitlock and Schluter motivate learning with interesting biological and medical examples; they emphasize intuitive understanding; and they focus on real data. The book covers basic topics in introductory statistics, including graphs, confidence intervals, hypothesis testing, comparison of means, regression, and designing experiments. It also introduces the principles behind such modern topics as likelihood, linear models, meta-analysis and computer-intensive methods. Instructors and students consistently praise the book's clear and engaging writing, strong visualization techniques, and its variety of fascinating and relevant biological examples.

    The Landscape of History provides a searching look at the historian's craft, as well as a strong argument for why a historical consciousness should matter to us today.Gaddis points out that while the historical method is more sophisticated than most historians realize, it doesn't require unintelligible prose to explain. Like cartographers mapping landscapes, historians represent what they can never replicate. In doing so, they combine the techniques of artists, geologists, paleontologists, and evolutionary biologists. Their approaches parallel, in intriguing ways, the new sciences of chaos, complexity, and criticality. They don't much resemble what happens in the social sciences, where the pursuit of independent variables functioning with static systems seems increasingly divorced from the world as we know it. So who's really being scientific and who isn't? This question too is one Gaddis explores, in ways that are certain to spark interdisciplinary controversy.Written in the tradition of Marc Bloch and E.H. Carr, The Landscape of History is at once an engaging introduction to the historical method for beginners, a powerful reaffirmation of it for practitioners, a startling challenge to social scientists, and an effective skewering of post-modernist claims that we can't know anything at all about the past. It will be essential reading for anyone who reads, writes, teaches, or cares about history.

    Arnold, CHOICE"The book provides readers with a clear, sympathetic and unbiased understanding of the four conflicting visions of curriculum that will enable them to more productively interact with educators who might hold different beliefs. The book stimulates readers to better understand their own beliefs and also to provide them with an understanding of alternate ways of thinking about the fundamental goals of education" --SIRREADALOT.ORG"A much needed, insightful view of alternative curriculum orientations. This is an exceptionally written book that will be useful to teachers, curriculum workers, and school administrators."--Marc Mahlios, University of Kansas"Curriculum Theory: Conflicting Visions and Enduring Concerns is a thought provoking text that invites self-analysis."--Lars J. Helgeson, University of North DakotaCurriculum Theory: Conflicting Visions and Enduring Concerns presents a clear, unbiased, and rigorous description of the major curriculum philosophies that have influenced educators and schooling over the last century. Author Michael Stephen Schiro analyzes four educational visions--Scholar Academic, Social Efficiency, Learner Centered, and Social Reconstruction--to enable readers to reflect on their own educational beliefs and allow them to more productively interact with educators who might hold different beliefs.Key FeaturesProvides a historical perspective on the origins of curriculum ideologies: The book places our current educational debates and issues in a historical context of enduring concerns.Offers a model of how educational movements can be critically analyzed: Using a post-structuralist perspective, this model enables readers to more effectively contribute to the public debate about educational issues.Pays careful attention to the way language is used by educators to give meaning to frequently unspoken assumptions: The text's examination helps readers better understand curricular disagreements that occur in schools.Highlights the complexities of curriculum work in a social context: With an understanding of the ideological pressures exerted on them by society and colleagues, readers can put these pressures in perspective and maintain their own values, beliefs, and practices.Intended AudienceThis book is designed as a supplemental text for advanced undergraduate and graduate courses such as Curriculum Theory, Introduction to Curriculum and Instruction, Curriculum Philosophy, and Curriculum Theory and Practice in the department of education.Talk to the author! schiro@bc.eduTo visit the author's web site, please visit: http: //www2.bc.edu/ schiro/sage.html.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    It discusses neuroanatomy, cell and molecular mechanisms and signaling through a cognitive approach to behaviour. It features an expanded treatment of the nervous system, neurological and psychiatric diseases and perception.

    The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression.Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you're a beginner, R Cookbook will help get you started. If you're an experienced data programmer, it will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process.Create vectors, handle variables, and perform other basic functionsInput and output dataTackle data structures such as matrices, lists, factors, and data framesWork with probability, probability distributions, and random variablesCalculate statistics and confidence intervals, and perform statistical testsCreate a variety of graphic displaysBuild statistical models with linear regressions and analysis of variance (ANOVA)Explore advanced statistical techniques, such as finding clusters in your dataWonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language--one practical example at a time.--Jeffrey Ryan, software consultant and R package author

    Covering every disorder routinely encountered in clinical practice, Frances provides the appropriate ICD-9-CM code for each one (the same code utilized in the DSM), a useful screening question, a colorful descriptive prototype, lucid diagnostic tips, and a discussion of other disorders that must be ruled out. The book closes with an index of the most common presenting symptoms, listing possible diagnoses that must be considered for each. Frances was instrumental in the development of past editions of the DSM and provides helpful cautions on questionable aspects of DSM-5.

    There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again for the classroom or for self-study.Principles of Statistics was created primarily for the student of natural sciences, the social scientist, the undergraduate mathematics student, or anyone familiar with the basics of mathematical language. It assumes no previous knowledge of statistics or probability; nor is extensive mathematical knowledge necessary beyond a familiarity with the fundamentals of differential and integral calculus. (The calculus is used primarily for ease of notation; skill in the techniques of integration is not necessary in order to understand the text.)Professor Bulmer devotes the first chapters to a concise, admirably clear description of basic terminology and fundamental statistical theory: abstract concepts of probability and their applications in dice games, Mendelian heredity, etc.; definitions and examples of discrete and continuous random variables; multivariate distributions and the descriptive tools used to delineate them; expected values; etc. The book then moves quickly to more advanced levels, as Professor Bulmer describes important distributions (binomial, Poisson, exponential, normal, etc.), tests of significance, statistical inference, point estimation, regression, and correlation. Dozens of exercises and problems appear at the end of various chapters, with answers provided at the back of the book. Also included are a number of statistical tables and selected references.

    The Twelfth Edition's hallmark continues to be its pioneering integration of the proven-effective SQ4R learning system (Survey, Question, Read, Reflect, Review, Recite), which promotes critical thinking as it guides students step-by-step to an understanding of psychology's broad concepts and diversity of topics. Throughout every chapter, these active learning tools—together with the book's example-laced writing style, discussions of positive psychology, cutting-edge coverage of the field's new research findings, and excellent media resources—ensure that students find the study of psychology fascinating, relevant, and above all, accessible.

    Library and information science students and professionals will find the background and concepts they need to meet today's - and tomorrow's - challenges. TABLE OF CONTENTS: 1. The Information Infrastructure: Libraries in Context; 2. Information Science: A Service Perspective; 3. Redefining the Library: The Impacts and Implications of Technological Change; 4. Information Policy: Stakeholders and Agendas; 5. Information Policy as Library Policy: Intellectual Freedom; 6. Information Organization: Issues and Techniques; 7. From Past to Present: The Library s Mission and Its Values; 8. Ethics and Standards: Professional Practices in Library and Information Science; 9. The Library as Institution: An Organizational View, and 10. Librarianship: An Evolving Profession.

    You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples--ready for immediate application to your next graph or presentation.Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to:Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data--Storytelling with Data will give you the skills and power to tell it!