The book begins with an introduction to the language of statistics and then covers descriptive statistics and inferential statistics. Throughout, the author offers readers:- Difficulty Rating Index for each chapter′s material- Tips for doing and thinking about a statistical technique- Top tens for everything from the best ways to create a graph to the most effective techniques for data collection- Steps that break techniques down into a clear sequence of procedures- SPSS tips for executing each major statistical technique- Practice exercises at the end of each chapter, followed by worked out solutions.The book concludes with a statistical software sampler and a description of the best Internet sites for statistical information and data resources. Readers also have access to a website for downloading data that they can use to practice additional exercises from the book. Students and researchers will appreciate the book′s unhurried pace and thorough, friendly presentation.

    Through lively re-creations of actual workshops that he regularly conducts for students and teachers, Blau invites his readers to become active participants in workshops on such topics as:helping students read more difficult texts than they think they can readwhere interpretations come fromthe problem of background knowledge in teaching classic textshow to deal with competing and contradictory interpretationswhat's worth saying about a literary textbalancing respect for readers with respect for texts and intellectual authorityensuring that literary discussions are lively and productivehow to develop valuable and engaging writing assignments.Each workshop includes reflections on what transpired and a discussion of the workshop's rationale and outcomes in the larger context of an original and practice-based theory of literary competence and instruction.

    It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought.Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.”Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

    For this reason Nancy Vyhmeister brought in Terry Robertson, Seminary Librarian at Andrews University and professor of the seminary master’s level research courses. His expertise in library, computers, and the Internet are invaluable to the book.In addition to substantial, current information on electronic resources and online research, this third edition preserves all of the features of the original editions, now presented in a newly revised, more logical order.

    Though the answers may seem simple, their profound implications make the prisoner's dilemma one of the great unifying concepts of science. Watching players bluff in a poker game inspired John von Neumann--father of the modern computer and one of the sharpest minds of the century--to construct game theory, a mathematical study of conflict and deception. Game theory was readily embraced at the RAND Corporation, the archetypical think tank charged with formulating military strategy for the atomic age, and in 1950 two RAND scientists made a momentous discovery.Called the prisoner's dilemma, it is a disturbing and mind-bending game where two or more people may betray the common good for individual gain. Introduced shortly after the Soviet Union acquired the atomic bomb, the prisoner's dilemma quickly became a popular allegory of the nuclear arms race. Intellectuals such as von Neumann and Bertrand Russell joined military and political leaders in rallying to the preventive war movement, which advocated a nuclear first strike against the Soviet Union. Though the Truman administration rejected preventive war the United States entered into an arms race with the Soviets and game theory developed into a controversial tool of public policy--alternately accused of justifying arms races and touted as the only hope of preventing them.A masterful work of science writing, Prisoner's Dilemma weaves together a biography of the brilliant and tragic von Neumann, a history of pivotal phases of the cold war, and an investigation of game theory's far-reaching influence on public policy today. Most important, Prisoner's Dilemma is the incisive story of a revolutionary idea that has been hailed as a landmark of twentieth-century thought.

    Through mechanisms designed by Southern Democrats that specifically excluded maids and farm workers, the gap between blacks and whites actually widened despite postwar prosperity. In the words of noted historian Eric Foner, "Katznelson's incisive book should change the terms of debate about affirmative action, and about the last seventy years of American history."

    Slavery produced centuries of physical, psychological and spiritual injury. Post Traumatic Slave Syndrome: America's Legacy of Enduring Injury and Healing lays the groundwork for understanding how the past has influenced the present, and opens up the discussion of how we can use the strengths we have gained to heal.

    Like Henry Petroski's The Pencil, Scrolling Forward takes a common, everyday object, the document, and illuminates what it reveals about us--our work, our values, our relationships--both in the past and as we move into the digital age.

    Using the cross-disciplinary approaches of speech and social psychology, Knapp and Hall center on how nonverbal communication research affects a wide variety of academic interests. It is the most comprehensive, most readable compendium of research and theory on nonverbal communication available. It is the standard reference in this area.

    Gigabytes, exabytes (that’s one quintillion bytes) of data are sitting on servers across the world. So how can we start to access this explosion of information, this “big data,” and what can it tell us?   Erez Aiden and Jean-Baptiste Michel are two young scientists at Harvard who started to ask those questions. They teamed up with Google to create the Ngram Viewer, a Web-based tool that can chart words throughout the massive Google Books archive, sifting through billions of words to find fascinating cultural trends. On the day that the Ngram Viewer debuted in 2010, more than one million queries were run through it.   On the front lines of Big Data, Aiden and Michel realized that this big dataset—the Google Books archive that contains remarkable information on the human experience—had huge implications for looking at our shared human history. The tool they developed to delve into the data has enabled researchers to track how our language has evolved over time, how art has been censored, how fame can grow and fade, how nations trend toward war. How we remember and how we forget. And ultimately, how Big Data is changing the game for the sciences, humanities, politics, business, and our culture.

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

    In Rules of Play Katie Salen and Eric Zimmerman present a much-needed primer for this emerging field. They offer a unified model for looking at all kinds of games, from board games and sports to computer and video games. As active participants in game culture, the authors have written Rules of Play as a catalyst for innovation, filled with new concepts, strategies, and methodologies for creating and understanding games. Building an aesthetics of interactive systems, Salen and Zimmerman define core concepts like play, design, and interactivity. They look at games through a series of eighteen game design schemas, or conceptual frameworks, including games as systems of emergence and information, as contexts for social play, as a storytelling medium, and as sites of cultural resistance.Written for game scholars, game developers, and interactive designers, Rules of Play is a textbook, reference book, and theoretical guide. It is the first comprehensive attempt to establish a solid theoretical framework for the emerging discipline of game design.

    Only now, with the hindsight of the half-century since his death, can we assess his true legacy to current thought. As an experienced psychiatrist himself, Anthony Storr offers a lucid and objective look at Freud's major theories, evaluating whether they have stood the test of time, and in the process examines Freud himself in light of his own ideas. An excellent introduction to Freud's work, this book will appeal to all those broadly curious about psychoanalysis, psychology, and sociology. About the Series: Combining authority with wit, accessibility, and style, Very Short Introductions offer an introduction to some of life's most interesting topics. Written by experts for the newcomer, they demonstrate the finest contemporary thinking about the central problems and issues in hundreds of key topics, from philosophy to Freud, quantum theory to Islam.

    It is not about terrorism, the holocaust, or understanding death. They are the framework for this heartwarming story about a never-a-serious-thought high school senior and his best friend, a Deaf-blind, legless old man, who teaches him how to capture and hold, The Pristine American Dream. Pristine, "Characteristics of the earliest period or condition: original: still pure: uncorrupted: unspoiled [Pristine beauty]." Webster's New World Dictionary. Sometime, somehow, somewhere, we, as a people, stopped living and dreaming The Pristine American Dream as our Founding Fathers knew it. Like colors fading from a handkerchief long forgotten on a cedar post, the Dream has faded from our thoughts and aspirations. The change has been imperceptible, yet over time all of the brilliance has faded to the dull, uninspiring and common. The Pristine American Dream has taken on a different hue. To some, the American Dream has become a passionate search for easy wealth by hitting it big in the lottery, sweepstakes, a big lawsuit, or receiving an inheritance. To others it is landing a professional sports contract, or achieving prominence in politics, business or popularity without any thought to inherent rights. As important as these achievements may be to some people, The Pristine American Dream is much better. This story showcases The Pristine American Dream, which is those inalienable or inherent rights guaranteed to each American by virtue of their birth, and the diligence, hard work and determination required to obtain and enjoy the privileges of life. Simply put, inherent rights are the rights to be and to do good. Everything that is good is right, an inherent right. Nobody ever has the right to do bad; they only have the power to choose it. Many people see goodness as the result of religious dedication instead of the catalyst that fires the furnace of happiness. No matter what circumstances' individuals, families, communities or nations find themselves in, they always enjoy more peace of mind and happiness when they maintain their inherent rights. Privileges are the sweet things of life for which one must work to receive. This is a fiction story. The setting is Declo, Idaho during the years of 1966 and 1967. All the characters are fiction, but like many great fiction characters they may resemble living or dead individuals whose lives have impacted that of the author. Most family names are indigenous to the Declo community, yet there should not be any inference made that any of the characters are living or have ever lived. There are, however, certain authenthic individuals who make cameo appearances to add color to its historical setting.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details