This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics--particularly in machine learning, scientific modeling, and artificial life--and reviews a broad span of research, including the work of Mitchell and her colleagues.The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting general purpose nature of genetic algorithms as search methods that can be employed across disciplines.An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.

    The book makes clear that applied microeconometrics is about the estimation of marginal and treatment effects, and that parametric estimation is simply a means to this end. It also clarifies the distinction between causality and statistical association. The book focuses specifically on cross section and panel data methods. Population assumptions are stated separately from sampling assumptions, leading to simple statements as well as to important insights. The unified approach to linear and nonlinear models and to cross section and panel data enables straightforward coverage of more advanced methods. The numerous end-of-chapter problems are an important component of the book. Some problems contain important points not fully described in the text, and others cover new ideas that can be analyzed using tools presented in the current and previous chapters. Several problems require the use of the data sets located at the author's website.

    They will also develop a deeper understanding of the many interconnections that exist among the different areas of psychology. Goodwin's book not only provides accounts of the lives and contributions of psychology's pioneers set into historical context; it also contains original writings by these psychologists, interwoven with informative comments from the author. The text is written in a conversational and engaging style with discrete attention to recent scholarship in the history of psychology, especially that of the past 150 years.

    Each case includes an extended discussion, definition of terms, clinical pearls, and USMLE format review questions. This interactive learning system is proven to improve shelf-exam scores and helps students to learn in the context of real patients insted of simply memorizing.

    This book provides a modern introduction to the main principles that are foundational to thermal physics, thermodynamics and statistical mechanics. The key concepts are carefully presented in a clear way, and new ideas are illustrated with copious worked examples as well as a description of the historical background to their discovery. Applications are presented to subjects as diverse as stellar astrophysics, information and communication theory, condensed matter physics and climate change. Each chapter concludes with detailed exercises.

    The clarity and eloquence of the presentation make it popular with teachers and students alike. The text aims to expand the reader's view of the field and to present standard material in a novel way. All of the most important topics in the field are covered with a fresh perspective, including iterative methods for systems of equations and eigenvalue problems and the underlying principles of conditioning and stability. Presentation is in the form of 40 lectures, which each focus on one or two central ideas. The unity between topics is emphasized throughout, with no risk of getting lost in details and technicalities. The book breaks with tradition by beginning with the QR factorization - an important and fresh idea for students, and the thread that connects most of the algorithms of numerical linear algebra.

    Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges.It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.

    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.

    This overview has enabled students to make sense more easily of what instructors are doing when they produce proofs, theorems and formulas.

     Douglas Montgomery arms readers with the most effective approach for learning how to design, conduct, and analyze experiments that optimize performance in products and processes. He shows how to use statistically designed experiments to obtain information for characterization and optimization of systems, improve manufacturing processes, and design and develop new processes and products. You will also learn how to evaluate material alternatives in product design, improve the field performance, reliability, and manufacturing aspects of products, and conduct experiments effectively and efficiently. Discover how to improve the quality and efficiency of working systems with this highly-acclaimed book. This 6th Edition: Places a strong focus on the use of the computer, providing output from two software products: Minitab and DesignExpert. Presents timely, new examples as well as expanded coverage on adding runs to a fractional factorial to de-alias effects. Includes detailed discussions on how computers are currently used in the analysis and design of experiments. Offers new material on a number of important topics, including follow-up experimentation and split-plot design. Focuses even more sharply on factorial and fractional factorial design.

    These vignettes serve as springboards to many telling perspectives: simple arithmetic puts life-long habits in a dubious new light; higher dimensional geometry helps us see that we're all rather peculiar; nonlinear dynamics explains the narcissism of small differences cascading into very different siblings; logarithms and exponentials yield insight on why we tend to become bored and jaded as we age; and there are tricks and jokes, probability and coincidences, and much more.For fans of Paulos or newcomers to his work, this witty commentary on his life--and yours--is fascinating reading.From the Trade Paperback edition.

    The illustrations provide some of the best quality and most varied examples of skin conditions important to any health care pforessional dealing with skin problems.

    Imagine that you face three doors, behind one of which is a prize. You choose one but do not open it. The host--call him Monty Hall--opens a different door, alwayschoosing one he knows to be empty. Left with two doors, will you do better by sticking with your first choice, or by switching to the other remaining door? In this light-hearted yet ultimately serious book, Jason Rosenhouse explores the history of this fascinating puzzle. Using a minimum ofmathematics (and none at all for much of the book), he shows how the problem has fascinated philosophers, psychologists, and many others, and examines the many variations that have appeared over the years. As Rosenhouse demonstrates, the Monty Hall Problem illuminates fundamental mathematical issuesand has abiding philosophical implications. Perhaps most important, he writes, the problem opens a window on our cognitive difficulties in reasoning about uncertainty.

    Contents include: 'Personality Theory in Context', 'Cognitive Personality Theories', 'An Introduction to Intelligence', 'The Application of Personality and Intelligence in Education and the Workplace', 'Optimism', 'Interpersonal Relationships' and 'Psychometric Testing'.

    It gives clear descriptions of linear systems and uses mathematics not only to prove axiomatic theory, but also to enhance physical and intuitive understanding.