But all too often, these numbers are wrong. This book is a lively guide to spotting bad statistics and learning to think critically about these influential numbers. Damned Lies and Statistics is essential reading for everyone who reads or listens to the news, for students, and for anyone who relies on statistical information to understand social problems.Joel Best bases his discussion on a wide assortment of intriguing contemporary issues that have garnered much recent media attention, including abortion, cyberporn, homelessness, the Million Man March, teen suicide, the U.S. census, and much more. Using examples from the New York Times, the Washington Post, and other major newspapers and television programs, he unravels many fascinating examples of the use, misuse, and abuse of statistical information.In this book Best shows us exactly how and why bad statistics emerge, spread, and come to shape policy debates. He recommends specific ways to detect bad statistics, and shows how to think more critically about "stat wars," or disputes over social statistics among various experts. Understanding this book does not require sophisticated mathematical knowledge; Best discusses the most basic and most easily understood forms of statistics, such as percentages, averages, and rates.This accessible book provides an alternative to either naively accepting the statistics we hear or cynically assuming that all numbers are meaningless. It shows how anyone can become a more intelligent, critical, and empowered consumer of the statistics that inundate both the social sciences and our media-saturated lives.

    Stewart's Calculus is successful throughout the world because he explains the material in a way that makes sense to a wide variety of readers. His explanations make ideas come alive, and his problems challenge, to reveal the beauty of calculus. Stewart's examples stand out because they are not just models for problem solving or a means of demonstrating techniques--they also encourage readers to develp an analytic view of the subject. This edition includes new problems, examples, and projects.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    Since then it has become the standard reference in the field. In this completely revised third edition, Bryson updates his perennial bestseller to help today's leaders enhance organizational effectiveness. This new edition: Features the Strategy Change Cycle--a proven planning process used by a large number of organizations Offers detailed guidance on implementing the planning process and includes specific tools and techniques to make the process work in any organization Introduces new material on creating public value, stakeholder analysis, strategy mapping, balanced scorecards, collaboration, and more Includes information about the organizational designs that will encourage strategic thought and action throughout the entire organization Contains a wealth of updated examples and cases

    Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data.

    Each self-contained chapter consists of three sections. The first describes the statistic, including how it is used and what information it provides. The second section reviews how it works, how to calculate the formula, the strengths and weaknesses of the technique, and the conditions needed for its use. The final section provides examples that use and interpret the statistic. A glossary of terms and symbols is also included.New features in the second edition include:an interactive CD with PowerPoint presentations and problems for each chapter including an overview of the problem's solution; new chapters on basic research concepts including sampling, definitions of different types of variables, and basic research designs and one on nonparametric statistics; more graphs and more precise descriptions of each statistic; and a discussion of confidence intervals.This brief paperback is an ideal supplement for statistics, research methods, courses that use statistics, or as a reference tool to refresh one's memory about key concepts. The actual research examples are from psychology, education, and other social and behavioral sciences.Materials formerly available with this book on CD-ROM are now available for download from our website www.psypress.com. Go to the book's page and look for the 'Download' link in the right-hand column.

    Updated web links and expanded appendices provide cutting edge information on action research along with new case studies and examples.

    It shows teachers how to create an environment in which technology can effectively enhance learning. It contains a technology integration framework that builds on research and the TIP model.

    New features include: a new chapter on queer theory; every chapter has been revised with new introductions with appropriate new critical vocabulary, critical terms, further readings sections, and web sites; new student essays; structuralism and deconstruction have been combined into one section to make the material clearer and more streamlined; and the addition of Plotinus, Giovanni Boccaccio, Joseph Addison, Percy Pysshe Shelley, and Mikhail Bakhtin.

    It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable. Professor of Computer Science at the UCLA, Judea Pearl is the winner of the 2008 Benjamin Franklin Award in Computers and Cognitive Science.

    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

    Child Development

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    But what happens when this system of adjusting emotions is adapted to commercial purposes? Hochschild examines the cost of this kind of "emotional labor." She vividly describes from a humanist and feminist perspective the process of estrangement from personal feelings and its role as an "occupational hazard" for one-third of America's workforce.

    People don't listen to advertisements, they listen to their peers. But why do people talk about certain products and ideas more than others? Why are some stories and rumors more infectious? And what makes online content go viral? Wharton marketing professor Jonah Berger has spent the last decade answering these questions. He's studied why New York Times articles make the paper's own Most E-mailed List, why products get word of mouth, and how social influence shapes everything from the cars we buy to the clothes we wear to the names we give our children. In this book, Berger reveals the secret science behind word-of-mouth and social transmission. Discover how six basic principles drive all sorts of things to become contagious, from consumer products and policy initiatives to workplace rumors and YouTube videos.Contagious combines groundbreaking research with powerful stories. Learn how a luxury steakhouse found popularity through the lowly cheese-steak, why anti-drug commercials might have actually increased drug use, and why more than 200 million consumers shared a video about one of the seemingly most boring products there is: a blender. If you've wondered why certain stories get shared, e-mails get forwarded, or videos go viral, Contagious explains why, and shows how to leverage these concepts to craft contagious content. This book provides a set of specific, actionable techniques for helping information spread - for designing messages, advertisements, and information that people will share. Whether you're a manager at a big company, a small business owner trying to boost awareness, a politician running for office, or a health official trying to get the word out, Contagious will show you how to make your product or idea catch on.