A six-step model offers invaluable assistance for selecting a topic, searching the literature, developing arguments, surveying the literature, critiquing the literature, and writing the literature review.

    Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

    The reorganized text reflects a more balanced coverage of both quantitative and qualitative methodologies. Unique features of this revised edition include an approachable text your students won't mind reading and will want to keep; the accessible writing style, clear and concise explanations, and humorous tone demystify the research process; eleven cumulative Tasks throughout the text provide practice and skill development in doing research, step by step; expanded coverage of qualitative research and mixed methods Chapter 16 covering Narrative Research, and Chapter 17 covering Ethnographic Research, are new to this edition. Chapter 19, Mixed Methods, is also new to this edition. There is an expanded coverage of technology and an increased coverage of how to use technology in the research process. The 39 articles provided in the package (Text, Student Study Guide, and Website) are accompanied by a variety of pedagogical aids to help students learn to read research. research.

    It examines general patterns of human behavior in age-graded periods, sources of diversity in life course trajectories, and unique life stories. It is multidimensional in scope and current in theory and research. This completely revised second edition maintains the use of case studies to help students appreciate the diversity of life course trajectories, and all chapters have been updated to reflect social trends and new developments in theory and research. To reflect the trend toward finer gradations in life phases, this edition addresses nine age-graded periods instead of the six presented in the first edition: Conception, Pregnancy, and Birth; Infancy and Toddlerhood; Early Childhood; Middle Childhood; Adolescence; Young Adulthood; Middle Adulthood; Late Adulthood; and Very Late Adulthood. The Changing Life Course is the companion volume to Person and Environment (ISBN 0-7619-8765-7). The two volumes are also available as a Two-Volume Kit (ISBN 0-7619-8803-3). An Instructor′s Manual containing chapter summaries, suggested classroom activities and discussions, and essay and multiple choice questions is also available (ISBN: 0-7619-8804-1).

    Rossi, Mark W. Lipsey, and Howard E. Freeman first published Evaluation: A Systematic Approach, more than 90,000 readers have considered it the premier text on how to design, implement, and appraise social programs through evaluation. In this, the completely revised Seventh Edition, authors Rossi and Lipsey include the latest techniques and approaches to evaluation as well as guidelines to tailor evaluations to fit programs and social contexts.With decades of hands-on experience conducting evaluations, the authors provide scores of examples to help students understand how evaluators deal with various critical issues. They include a glossary of key terms and concepts, making this the most comprehensive and authoritative evaluation text available.Thoroughly revised, the Seventh Edition now includes* Substantially more attention to outcome measurement* Lengthy discussions of program theory, including a section about detecting program effects and interpreting their practical significance* An augmented and updated discussion of major evaluation designs* A detailed exposition of meta-analysis as an approach to the synthesis of evaluation studies* Alternative approaches to evaluation* Examples of successful evaluations* Discussions of the political and social contexts of evaluation

    Essentially, you make an initial guess, and then get more data to improve it. Bayes Theorem, or Bayes Rule, has a ton of real world applications, from estimating your risk of a heart attack to making recommendations on Netflix But It Isn't That Complicated This book is a short introduction to Bayes Theorem. It is only 15 pages long, and is intended to show you how Bayes Theorem works as quickly as possible. The examples are intentionally kept simple to focus solely on Bayes Theorem without requiring that the reader know complicated probability distributions. If you want to learn the basics of Bayes Theorem as quickly as possible, with some easy to duplicate examples, this is a good book for you.

    In this new Seventh Edition of his perennially successful social research text, author Russell K. Schutt continues to make research come alive through stories that illustrate the methods presented in each chapter, and hands-on exercises that help students learn by doing. Investigating the Social World helps readers understand research methods as an integrated whole, appreciate the value of both qualitative and quantitative methodologies, and understand the need to make ethical research decisions. New to this Edition: * upgraded coverage of research methods to include the spread of cell phones and the use of the Internet, including expanded coverage of Web surveys * larger page size in full color allows for better display of pedagogical features * new 'Research in the News' boxes included within chapters * more international examples * expanded statistics coverage now includes more coverage of inferenctial statistics and regression analysi

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    In this lively and groundbreaking new book, economist Ian Ayres shows how today's best and brightest organizations are analyzing massive databases at lightening speed to provide greater insights into human behavior. They are the Super Crunchers. From internet sites like Google and Amazon that know your tastes better than you do, to a physician's diagnosis and your child's education, to boardrooms and government agencies, this new breed of decision makers are calling the shots. And they are delivering staggeringly accurate results. How can a football coach evaluate a player without ever seeing him play? Want to know whether the price of an airline ticket will go up or down before you buy? How can a formula outpredict wine experts in determining the best vintages? Super crunchers have the answers. In this brave new world of equation versus expertise, Ayres shows us the benefits and risks, who loses and who wins, and how super crunching can be used to help, not manipulate us.Gone are the days of solely relying on intuition to make decisions. No businessperson, consumer, or student who wants to stay ahead of the curve should make another keystroke without reading Super Crunchers.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    Using actual unfinished, "working" notes as examples, they illustrate options for composing, reviewing, and working fieldnotes into finished texts. They discuss different organizational and descriptive strategies, including evocation of sensory detail, synthesis of complete scenes, the value of partial versus omniscient perspectives, and of first person versus third person accounts. Of particular interest is the author's discussion of notetaking as a mindset. They show how transforming direct observations into vivid descriptions results not simply from good memory but more crucially from learning to envision scenes as written. A good ethnographer, they demonstrate, must learn to remember dialogue and movement like an actor, to see colors and shapes like a painter, and to sense moods and rhythms like a poet.The authors also emphasize the ethnographer's core interest in presenting the perceptions and meanings which the people studied attach to their own actions. They demonstrate the subtle ways that writers can make the voices of people heard in the texts they produce. Finally, they analyze the "processing" of fieldnotes—the practice of coding notes to identify themes and methods for selecting and weaving together fieldnote excerpts to write a polished ethnography.This book, however, is more than a "how-to" manual. The authors examine writing fieldnotes as an interactive and interpretive process in which the researcher's own commitments and relationships with those in the field inevitably shape the character and content of those fieldnotes. They explore the conscious and unconscious writing choices that produce fieldnote accounts. And they show how the character and content of these fieldnotes inevitably influence the arguments and analyses the ethnographer can make in the final ethnographic tale.This book shows that note-taking is a craft that can be taught. Along with Tales of the Field and George Marcus and Michael Fisher's Anthropology as Cultural Criticism, Writing Ethnographic Fieldnotes is an essential tool for students and social scientists alike.

    It draws on Robert Weiss's thirty years of experience in interviewing and teaching others how to do it. The most effective interviews, says Weiss, rely on creating cooperation -- an open and trusting alliance between interviewer and respondent, dedicated to specific and honest accounts of both internal and external events. Against the eclectic background of his work in national sample surveys, studies based on semi-structured interviewing, and participant observation, Weiss walks the reader through the method of qualitative interview studies: sample selection, development of an interview guide, the conduct of the interview, analysis, and preparation of the data. Weiss gives examples of successful and less successful interviews and offers specific techniques and guidelines for the practitioner.

    Through statistics like these, we feel that we understand our fellow citizens. But remarkably, such data now woven into our social fabric became common currency only in the last century. Sarah Igo tells the story, for the first time, of how opinion polls, man-in-the-street interviews, sex surveys, community studies, and consumer research transformed the United States public.Igo argues that modern surveys, from the Middletown studies to the Gallup Poll and the Kinsey Reports, projected new visions of the nation: authoritative accounts of majorities and minorities, the mainstream and the marginal. They also infiltrated the lives of those who opened their doors to pollsters, or measured their habits and beliefs against statistics culled from strangers. Survey data underwrote categories as abstract as the average American and as intimate as the sexual self.With a bold and sophisticated analysis, Igo demonstrates the power of scientific surveys to shape Americans sense of themselves as individuals, members of communities, and citizens of a nation. Tracing how ordinary people argued about and adapted to a public awash in aggregate data, she reveals how survey techniques and findings became the vocabulary of mass society and essential to understanding who we, as modern Americans, think we are.

    The Fifth Edition features updated information throughout, including new theories and models such as the Healthy Action Process Approach (HAPA) and the Community Readiness Model (CRM), sections on grant writing and preparing a budget, real-life examples of marketing principles and processes, and a new classification system for evaluation approaches and designs. Health Education, Health Promotion, Health Educators, and Program Planning, Models for Program Planning in Health Promotion, Starting the Planning Process, Assessing Needs, Measurement, Measures, Measurement Instruments and Sampling, Mission Statement, Goals, and Objectives, Theories and Models Commonly Used for Health Promotion Interventions, Interventions, Community Organizing and Community Building, Identification and Allocation of Resources, Marketing: Making Sure Programs Respond to Wants and Needs of Consumers, Implementation: Strategies and Associated Concerns, Evaluation: An Overview, Evaluation Approaches and Designs, Data Analysis and Reporting. Intended for those interested in learning the basics of planning, implementing, and evaluating health promotion programs

    Gravetter, and co-author Lori-Ann B. Forzano have written a text for research methods that helps you see how interesting and exciting experimental and non-experimental research can be. Inviting and conversational, RESEARCH METHODS FOR THE BEHAVIORAL SCIENCES, Third Edition, leads you through the research process from start to finish. The text opens with tips and strategies for generating research ideas, moves to selecting measures and participants, and then offers an examination of research strategy and design. This step-by-step approach emphasizes the decisions researchers must make at each stage of the process. The authors avoid a "cookbook" approach to the facts by linking terminology with applied concepts; their "lecture in a book" style emphasizes discussion and explanation of topics. Each chapter ends with a set of exercises and activities.