Social research and statistics Books

Book SynopsisA Critical Introduction to Social Research is the new, updated and improved edition of A Short Introduction to Social Research. This book introduces students and researchers to the key ideas and issues that inform research practice. In it, Henn, Weinstein and Foard provide a clear and easy-to-understand route-map to help the reader plan their research project from beginning to end. A Critical Introduction is perfect for use on introductory methods courses and is also an invaluable guide for the first time researcher embarking on their own small-scale research project. This new second edition now features updated chapters which reflect recent debates and developments in the field, including: - New coverage of emancipatory and feminist approaches; - Comparative research methods, evaluation research, and action research; - Online research; - Glossary of key terms; - Revised further reading sections at the end of each chapter which include peer-reviewed research articles. This book aims to prepare students and new researchers for their research project. Brilliantly written throughout, this is your essential guide to the theory of research, the practice of research and the best ways to plan and manage your research.Trade ReviewPraise for the first edition: ′Henn et al mention in their introduction that their book has been "a long time in coming". The good news is that it has been time well spent′ - The Times Higher EducationTable of ContentsIntroduction What is Social Research? Critical Social Research Getting Started in Research: The Research Process Ethics in Social Research Documentary Sources, Official Statistics and Secondary Data Quantitative Approaches in Social Science Research Qualitative Approaches in Social Research The Analysis of Data Writing Up and Presenting Research Results Designing a Research Proposal Glossary

Read more less

Book SynopsisThe SAGE Handbook of Social Research Methods is a must for every social-science researcher. It charts the new and evolving terrain of social research methodology, covering qualitative, quantitative and mixed methods in one volume. The Handbook includes chapters on each phase of the research process: research design, methods of data collection, and the processes of analyzing and interpreting data. The volume maintains that there is much more to research than learning skills and techniques; methodology involves the fit between theory, research questions research design and analysis. The book also includes several chapters that describe historical and current directions in social research, debating crucial subjects such as qualitative versus quantitative paradigms, how to judge the credibility of types of research, and the increasingly topical issue of research ethics. The Handbook serves as an invaluable resource for approaching research with an open mind. This volume maps the field of social research methods using an approach that will prove valuable for both students and researchers.Table of ContentsSocial Research in Changing Social Conditions PART ONE: DIRECTIONS IN SOCIAL RESEARCH The End of the Paradigm Wars? - Alan Bryman The History of Social Research Methods - Marja Alastalo Assessing Validity in Social Research - Martyn Hammersley Ethnography and Audience - Karen Armstrong Social Research and Social Practice in Post-Positivist Society - Pekka Sulkunen From Questions of Methods to Epistemological Issues - Ann Nilsen The Case of Biographical Research Research Ethics in Social Science - Celia B. Fisher and Andrea E. Anushko PART TWO: RESEARCH DESIGNS The Core Analytics of Randomized Experiments for Social Research - H S Bloom Better Quasi-Experimental Practice - Thomas D. Cook and Vivian Wong Sample Size Planning with Applications to Multiple Regression - Ken Kelly and Scott E. Maxwell Power and Accuracy for Omnibus and Targeted Effects Re-Conceptualizing Generalization in Qualitative Research - Giampietro Gobo Old Issues in a New Frame Case Study in Social Research - Linda Mabry Longitudinal and Panel Studies - Janet Holland, Rachel Thomson and Jane Elliott Comparative and Cross-National Designs - David de Vaus PART THREE: DATA COLLECTION AND FIELDWORK Modern Measurement in the Social Sciences - James A. Bovaird and Susan E. Embretson Natural and Contrived Data - Susan Speer Self Administered Questionnaires and Standardized Interviews - Edith de Leeuw Qualitative Interviewing and Feminist Research - Andrea Doucet and Natasha Mautner Biographical Methods - Joanna Bornat Focus Groups - Janet Smithson PART FOUR: TYPES OF ANALYSIS AND INTERPRETATION OF EVIDENCE An Introduction to the Multi Level Model for Change - Suzanne E. Graham, Judith D. Singer and John B. Willett Latent Variable Models of Social Research Data - Rick H. Hoyle Equating Groups - Stephen West and Felix Thoemmes Discourse Analysis and Conversation Analysis - Charles Antaki Analyzing Narratives and Story-Telling - Matti Hyvärinen Reconstructing Grounded Theory - Kathy Charmaz Documents and Action - Lindsay Prior Video and the Analysis of Work and Interaction - Christian Heath and Paul Luff Secondary Analysis of Qualitative Data - Janet Heaton Secondary Analysis of Quantitative Data Sources - Angela Dale, Jo Wathan and Vanessa Wiggins Conducting a Meta Analysis - Erika A. Patall and Harris Cooper Synergy and Synthesis - Jane Fielding and Nigel Fielding Integrating Qualitative and Quantitative Data The Analytic Integration of Qualitative Data Sources - Ann Cronin, Victoria D. Alexander, Jane Fielding, Jo Moran-Ellis and Hilary Thomas Combining Different Types for Quantitative Analysis - Max Bergman Writing and Presenting Social Research - Amir Marvasti

Read more less

Book SynopsisThis new edition provides a scholarly and readable introduction to all the key qualitative and quantitative research methodologies and methods, enabling postgraduate and masters-level students and new researchers to reflect on which ones suit their needs and to receive guidance on how to find out more. With chapters written by experienced research practitioners, this second edition has been extensively expanded and updated. There are seven completely new chapters, as well as: - new material on literature reviews - a new introduction to quantitative methods - an expanded glossary - Weblinks with free access to a wide range of peer-reviewed journal articles - an annotated bibliography with conversational notes from authors in each chapter. This book will act as your ′expert friend′ throughout your research project, providing advice, explaining key concepts and the implications for your research design, and illustrating these with examples of real research studies.Trade ReviewPraise for the first edition: ′Not merely a how-to book, it reviews the conceptual framework of research methods in the social and behavioural sciences and provides tangible stories from the field that illustrate the application of specific techniques and the process of conducting research. . . . This work affords a concise overview of qualitative and quantitative methodologies in the social science. . . . Highly recommended′ - R.V. Labaree University of Southern California, CHOICETable of ContentsPART ONE: READING, REVIEWING AND REFLECTING Introduction Research in the Social Sciences - Bridget Somekh et al Working with Literatures - Barbara Kamler and Pat Thomson Ethical Issues in Generating Public Knowledge - Heather Piper and Helen Simons PART TWO: LISTENING, EXPLORING THE CASE AND THEORIZING Introduction Ethnography - Jo Frankham and Christina MacRae Research Diaries - Mary Louise Holly and Herbert Altrichter Case Study - Charlotte Chadderton and Harry Torrance Interviewing and Focus Groups - Rosaline SBarbour and John Schostak PART THREE: ADDRESSING ISSUES OF POWER AND RESEARCHING FOR IMPACT Introduction Feminist Methodologies - Diane Burns and Khatidja Chantler Critical Race Theory and Its Use in Social Science Research - Laurence Parker and Lorna Roberts Queer Theory / Lesbian and Gay Approaches - Gloria Filax et al Action Research - Susan Noffke and Bridget Somekh The Purpose, Practice and Politics of Sponsored Evaluations - Tineke Abma and Thomas A Schwandt PART FOUR: OBSERVING, QUERYING, INTERPRETING Introduction Grounded Theory - Juliet Corbin and Nicholas L Holt Understanding Phenomenology through Reverse Perspectives - Angie Titchen and Dawn Hobson Observation - Liz Jones and Bridget Somekh Discourse Analysis - Alison Lee and Alan Petersen Researching Online Practices - Colin Lankshear, Kevin M Leander and Michele Knobel PART FIVE: IDENTITY, COMMUNITY AND REPRESENTATION Introduction Life History and Narrative Methods - Scherto Gill and Ivor Goodson Social Semiotics and Multimodal Texts - Diane Mavers and Gunther Kress Communities of Practice - David Benzie and Bridget Somekh Activity Theory - Ines Langemeyer and Morten Nissen Researching Policy - Jill Blackmore and Hugh Lauder PART SIX: QUANTITATIVE METHODS: THEORIES AND PERSPECTIVES Introduction The Practices of Quantitative Methods - Kelvyn Jones The Positivist Paradigm in Contemporary Social Research: The Interface of Psychology, Method and Sociocultural Theory - Charles Crook and Dean Garratt Understanding and Describing Quantitative Data - Cathy Lewin Differences and Relationships in Quantitative Data - Sally Barnes and Cathy Lewin An Introduction to Statistical Modelling - Kelvyn Jones PART SEVEN: QUANTITATIVE METHODS IN ACTION Introduction Combining Qualitative and Quantitative Methods in Social Inquiry - Jennifer C Greene, Holly Kreider and Ellen Mayer Random Reflections on Modelling, Geography and Voting - Kelvyn Jones Methodological Issues in International Comparative Assessments of Educational Progress - W J Pelgrum Evaluating Literacy Advance in the Early Years of School - John Ainley Working Backwards: The Road Less Travelled in Quantitative Methodology - Brian Doig PART EIGHT: RESEARCHING IN POSTMODERN CONTEXTS Introduction Deconstruction - Erica Burman and Maggie Maclure From Hermeneutics to Post-Structuralism to Psychoanalysis - Tony Brown and Daniel Heggs From Structuralism to Post-Structuralism - Lee Miller, Joanne ′Bob′ Whalley and Ian Stronach Feminism/Post-Structuralism - Bronwen Davies and Suzanne Gannon

Read more less

Book Synopsis"Although written simply enough to be accessible to undergraduates, accomplished scholars are likely to appreciate it too. Reading it taught me quite a lot about a subject I thought I knew rather well." - Paul Vogt, Illinois State University "This book brings the art and science of building and applying innovative online research tools to students and faculty across the social sciences." - William H. Dutton, University of Oxford A comprehensive guide to the theory and practice of web Social Science. This book demonstrates how the web is being used to collect social research data, such as online surveys and interviews, as well as digital trace data from social media environments, such as Facebook and Twitter. It also illuminates how the advent of the web has led to traditional social science concepts and approaches being combined with those from other scientific disciplines, leading to new insights into social, political and economic behaviour. Situating social sciences in the digital age, this book aids: understanding of the fundamental changes to society, politics and the economy that have resulted from the advent of the web choice of appropriate data, tools and research methods for conducting research using web data learning how web data are providing new insights into long-standing social science research questions appreciation of how social science can facilitate an understanding of life in the digital age It is ideal for students and researchers across the social sciences, as well as those from information science, computer science and engineering who want to learn about how social scientists are thinking about and researching the web.Trade ReviewAckland′s Web Social Science is unique in being specifically designed for social science researchers. Although written simply enough to be accessible to undergraduates, accomplished scholars are likely to appreciate it too. Reading it taught me quite a lot about a subject I thought I knew rather well. -- Paul VogtA rare and timely entry to the growing body of quantitative Internet research. While most other works on the topic are written by and for scientists, this book represents a social science approach that is more accessible and applicable, with more attention to preparation, processing and interpretation of real-world data. Though primarily for readers in social science, business studies, policy analysts, and alike, the book blends traditional social science and emerging web science into a unique handbook of Internet research. -- Jonathan J. H. ZhuBrings the art and science of building and applying innovative online research tools to students and faculty across the social sciences. -- William H. DuttonProvides excellent chapters on how to study the Web from a social science research perspective. Although there are many books on theorizing the Internet and the Web, few tackle hands-on research issues. This two-part book (divided into a methods section and example studies) covers a wide range of research designs, tools and data types from many different social science perspectives (psychology, sociology, media studies, political studies and network science among others). Highly recommended for social science studies that want to use the Web to study social phenomena (the Web as a tool) and media studies that focus on the Web itself as a research object. -- Maurice VergeerThis book combines the technical terms with the social science perspective and some important topics in daily life related to private life, organisational, political and economic activities. It is appropriate for scientists and students in different areas – social, engineering, economic – every area that uses web for informing, promoting, exerting social influence and conducting studies. -- Stanislava Yordanova StoyanovaThe benefit-and the challenge- of this ambitious volume is that the author considers not only how web data are providing new insights into existing social science research questions, but also how social science can contribute to an understanding of life in the digital era...Overall, Ackland has much to offer researchers seeking to conduct Web social science research: in both the methods section and a section composed of concrete, useful examples, he examines varied research designs, tools and data types from diverse social science perspectives. Summing Up: Recommended. Graduate students and research/faculty. -- A.I. PiperAs a relative novice to web-based social research, I have been searching for a book that explains the concepts and different methodologies in accessible language; gives examples demonstrating the practical application of web methods; and does not neglect academic rigour and ethics. This one ticks all those boxes…Ackland’s book is comprehensive and, despite the technical topic, easy to read and understand. The book is particularly valuable for those new to web social science, while it will serve as a handy reference for those with experience in the field. -- Christine Bertram, research fellow at the Institute for Employment StudiesAn innovative book that is helpful for understanding new research questions on the impact of online networks and Internet use. This book can easily convince the reader of the importance of Internet-related research topics [and] it is a textbook that all students in social sciences would be able to read. -- Thierry PenardTable of ContentsChapter 1. Introduction PART ONE: WEB SOCIAL SCIENCE METHODS Chapter 2. Online Research Methods Dimensions and Modes of Online Research Online Surveys Online Interviews and Focus Groups Web Content Analysis Social Media Network Analysis Online Experiments Online Field Research Digital Trace Data: Ethics Chapter 3. Social Media Networks Social Networks: Concepts and Definitions Social Network Analysis Social Media Networks Social Networks, Information Networks and Communication Networks SNA Metrics for the Example School Friendship Network (advanced) Chapter 4. Hyperlink Networks Hyperlink Networks: Background Three Disciplinary Perspectives on Hyperlink Networks Tools for Hyperlink Network Research PART TWO: WEB SOCIAL SCIENCE EXAMPLES Chapter 5. Friendship Formation and Social Influence Homophily in Friendship Formation Social Influence Chapter 6. Organisational Collective Behaviour Collective Behaviour on the Web: Background Collective Action and Public Goods Networked Social Movements Chapter 7. Politics and Participation Visibility of Political Information Social and Political Engagement Political Homophily An Introduction to Power Laws (advanced) Chapter 8. Government and Public Policy Delivery of Information to Citizens Government Authority Public Policy Modelling Chapter 9. Production and Collaboration Peer Production and Information Public Goods Scholarly Activity and Communication Network Structure and Achievement Chapter 10. Commerce and Marketing Distribution of Product Sales Influence in Markets

Read more less

Book SynopsisThis concise and accessible book is a practical guide to qualitative classroom research, including extended case-studies of real research projects which serve as concrete examples of the advice provided. It gives a step by step account of how qualitative classroom research can be carried out and completed, with clear sets of guidelines for each stage and key points for consideration highlighted throughout. It can be read as a comprehensive guide to the research process, from beginning to end or as a resource to dip into to answer specific problems or queries. It is aimed at all college, university or school-based education students. In addition it is highly suitable for qualified teachers responding to the drive for greater evidence-based teaching in classrooms. Trade ReviewIts accessibility, lucidity and brevity are real strengths, as so many titles in the field of doing classroom research, though often very good, are frankly way too detailed and arcane for the needs of busy classroom practitioners – they need the essential basics, framed simply but not simplistically. I think Clive manages this so well – he’s always written with such spare beauty. -- Barry HymerIf I was back at university or doing classroom research again, this is a book I would welcome in my collection. It gives a good understanding of the purpose of research, both qualitative and quantitative, and who benefits. There are excellent links to inquiry and reading around the topics. I found it an easy read and not too long - just under 100 pages - making it very easy to dip in and out of as appropriate. There were useful examples linked to the content and drawn from actual research projects so carrying validity in the eye of the reader. This allows the reader to identify where they are and the best way forward in terms of research. The summary of key points at the end of chapters was helpful and made easy reference points to go back to. Overall, a very well-structured book. -- David Maynard, previously Director of The Cambridge PartnershipTable of ContentsIntroduction: Becoming a researcher A research report format: having a destination and a route Where to start: with theory or practice? Asking the research question Putting the research question to work: part 1 - developing observation guides Putting the research question to work: part 2 - developing interview guides Writing the research plan Reviewing the research process Organising the research data Analysing the data Evaluating the research report Appendix 1: A format for structuring the research report Appendix 2: Why research in real time matters Suggested further reading References

Read more less

Book Synopsis

Read more less

a huge range and FREE tracked UK delivery on ALL orders.

Read more less

Book SynopsisIn the light of better and more detailed administrative databases, this open access book provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy evaluation and monitoring, assess the causal effects of policy measures and report on best practices of successful data management and usage. Topics include data confidentiality, data linkage, and national practices in policy areas such as public health, education and employment. It offers scholars as well as practitioners from public administrations, consultancy firms and nongovernmental organizations insights into counterfactual impact evaluation methods and the potential of data-based policy and program evaluation. Trade Review“This book, edited by Nuno Crato and Paolo Paruolo, provides a thorough analysis of evaluation studies and is a valuable contribution for a reader seeking to gain an understanding of the literature on microdata issues and the use of the results related to policy evaluation. … the book could be very useful to scholars interested in regional development and regional policy effectiveness given the topics and the discussions included.” (Roberto Gabriele, Regional Studies, Vol. 53 (6), 2019)Table of ContentsIntroduction.- Part I: Microdata for Policy Research.- Part II: Microdata Access.- Part III: Counterfactual Studies.- Part IV: Use of Results.

Read more less

Book SynopsisThis book presents strategies for analyzing qualitative and mixed methods data with MAXQDA software, and provides guidance on implementing a variety of research methods and approaches, e.g. grounded theory, discourse analysis and qualitative content analysis, using the software. In addition, it explains specific topics, such as transcription, building a coding frame, visualization, analysis of videos, concept maps, group comparisons and the creation of literature reviews. The book is intended for masters and PhD students as well as researchers and practitioners dealing with qualitative data in various disciplines, including the educational and social sciences, psychology, public health, business or economics.Table of ContentsIntroduction: Analyzing Qualitative Data with Software.- Getting to Know the Interface of MAXQDA.- Setting up a Project and Importing Data.- Transcribing Audio and Video Recordings.- Exploring the Data.- Coding Text and PDF Files.- Coding Video Data, Audio Data, and Images.- Building a Coding Frame.- Working with Coded Segments and Memos.- Adding Variables and Quantifying Codes.- Working with Paraphrases and Summaries, Creating Case Overviews.- Comparing Cases and Groups, Discovering Interrelations and Using Visualizations.- Analyzing Mixed Methods Data.- Working with Bibliographic Information and Creating Literature Reviews.- Analyzing Focus Group Data.- Analyzing (Online) Survey Data with Closed and Open-Ended Questions.- MAXMaps: Creating Infographics and Concept Maps.- Collaborating in Teams.- Analyzing Intercoder Agreement.- Documenting and Archiving the Research Process.

Read more less

Book SynopsisThis book applies cutting-edge methods from cognitive and evolutionary theories to develop models of conflict between hierarchically-structured cognitive entities under circumstances of imprecision, uncertainty and stress. Characterized as friction and the fog-of-war by the Prussian military theorist Carl von Clausewitz, such conditions impair institutional cognition in real-time conflict and pose a real and continuing threat to organizations, such as the US military. In a linked collection of formal essays and a mathematical appendix, the book explores different aspects of cognitive and evolutionary process as conducted under the direction of doctrine that acts as a kind of genome for retention of what is learned through Lamarckian evolutionary selection pressures: armies and corporate entities learn from conflict, and incorporate that learning into their ongoing procedures. The book proposes models and policy solutions for strategic competence. A central feature of the book is a formal description of the famous OODA loop of the US military theorist John Boyd in terms of the Data Rate Theorem that links control and information theories. That description is expanded to cover more fully the impact of stochastic fog-of-war effects on tactical and operational scales of conflict. Subsequent chapters examine in more detail the role of doctrine, and the particular effect of embedding culture on cognitive and Lamarckian evolutionary processes associated with conflict on tactical, operational, and strategic scales and levels of organization. A scientifically sophisticated exercise in applied mathematics, history, evolutionary theory, and ecosystem theory, this book will be appropriate for researchers and students interested in defense, security, and international relations, as well as non-academic career professionals in government and industry.Table of ContentsChapter 1. Contrasting tactical and strategic dynamics.- Chapter 2. Doctrine and the fog-of-war.- Chapter 3. On asymmetric conflict.- Chapter 4. The Albigensian ground state.- Chapter 5. Can there be ‘Third Stream’ doctrine?- Chapter 6. Reconsidering doctrine and its discontents.- Chapter 7. Challenges to the US security doctrine of ‘Resilience’.- Chapter 8. Culture and the induction of emotional dysfunction on a Clausewitz landscape.- Chapter 9. Expected unexpecteds: Cambrian explosions in Lamarckian systems.- Chapter 10. Reconsidering Clausewitz Landscape dynamics.- Chapter 11. Failure of a paramilitary system: a case history of catastrophe.- Chapter 12. An emerging catastrophe: The weaponization of emotional sentience in AI.- Chapter 13. Final Remarks.- Chapter 14. Mathematical Appendix.

Read more less

Book SynopsisThis volume ambitiously applies sociological theory to create an understanding of aspects of survey methodology. It focuses on the interplay between sociology and survey methodology: what sociological theory and approaches can offer to survey research and vice versa. The volume starts with a focus on direct connections between sociological theories and their applications in survey research. It further presents cutting-edge, original research that applies the “sociological imagination” to substantive concerns important to sociologists, survey methodologists, and social scientists and includes issues such as health, immigration, race/ethnicity, gender and sexuality, and criminal justice.Table of Contents1. Why Survey Methodology Needs Sociology and Why Sociology Needs Survey Methodology.- Part I : Sociological Theory and Survey Methodology.- 2 Towards Survey Response Rate Theories That No Longer Pass Each Other Like Strangers in the Night.- 3. Advancing Theories of Socially Desirable Responding: How Identity Processes Influence Answers to “Sensitive Questions”.- 4. Culture and Response Behavior: An Overview of Cultural Mechanisms Explaining Survey Error.- 5. Translating Lessons from Status Characteristics and Expectation States Theory to Survey Methods.- Part II; Applications.- 6. Stigma and the Meaning of Social Desirability: Concealed Islamophobia in the Netherlands.- 7. Is Not Knowing the Same as Being Incorrect? An Examination of ‘Don’t Know’ Responses to Questions about Immigrant Population Size.- 8. Power, Culture and Item Nonresponse in Social Surveys.- 9. The Measurement of Sexual Attraction and Gender Expression: Cognitive Interviews with Queer Women.- 10. How Do Interviewers and Respondents Navigate Sexual Identity Questions in a CATI Survey?.- 11. Male/Female Is Not Enough: Adding Measures of Masculinity and Femininity to General Population Surveys.- 12. Correlates of Differences in Interactional Patterns among Black and White Respondents.- 13. Theories of Public Opinion Change Versus Stability and their Implications for Null Findings.- Conclusions and Future Directions for Understanding Survey Methodology.

Read more less

Book SynopsisAs explored in this open access book, higher education in STEM fields is influenced by many factors, including education research, government and school policies, financial considerations, technology limitations, and acceptance of innovations by faculty and students. In 2018, Drs. Ryoo and Winkelmann explored the opportunities, challenges, and future research initiatives of innovative learning environments (ILEs) in higher education STEM disciplines in their pioneering project: eXploring the Future of Innovative Learning Environments (X-FILEs). Workshop participants evaluated four main ILE categories: personalized and adaptive learning, multimodal learning formats, cross/extended reality (XR), and artificial intelligence (AI) and machine learning (ML). This open access book gathers the perspectives expressed during the X-FILEs workshop and its follow-up activities. It is designed to help inform education policy makers, researchers, developers, and practitioners about the adoption and implementation of ILEs in higher education.Table of Contents1. Introduction.- 2. X-FILEs Vision for personalized and Adaptive Learning.- 3. X-FILEs Vision for Multi-modal Learning Formats.- 4. X-FILEs Vision for Extended/Cross Reality (XR).- 5. X-FILEs Vision for Artificial Intelligence (AI) and Machine Learning (ML).- 6. Cross-Cutting Concerns.- 7. Epilogue.

Read more less

Book SynopsisThis book presents a guide for research methodology and scientific writing covering various elements such as finding research problems, writing research proposals, obtaining funds for research, selecting research designs, searching the literature and review, collection of data and analysis, preparation of thesis, writing research papers for journals, citation and listing of references, preparation of visual materials, oral and poster presentation in conferences, and ethical issues in research . Besides introducing library and its various features in a lucid style, the latest on the use of information technology in retrieving and managing information through various means are also discussed in this book. The book is useful for students, young researchers, and professionals.Table of Contents

Read more less

Book SynopsisThis book provides the student, researcher or practitioner with the tools to understand many of the most commonly used advanced statistical analysis tools in criminology and criminal justice, and also to apply them to research problems. The volume is structured around two main topics, giving the user flexibility to find what they need quickly. The first is “the general linear model” which is the main analytic approach used to understand what influences outcomes in crime and justice. It presents a series of approaches from OLS multivariate regression, through logistic regression and multi-nomial regression, hierarchical regression, to count regression. The volume also examines alternative methods for estimating unbiased outcomes that are becoming more common in criminology and criminal justice, including analyses of randomized experiments and propensity score matching. It also examines the problem of statistical power, and how it can be used to better design studies. Finally, it discusses meta analysis, which is used to summarize studies; and geographic statistical analysis, which allows us to take into account the ways in which geographies may influence our statistical conclusions.Table of ContentsChapter 1. Introduction.- Chapter 2. Multiple Regression- Chapter 3. Multiple Regression: Additional Topics.- Chapter 4. Logistic Regression.- Chapter 5. Multivariate Regression With Multiple Category Nominal or Ordinal Measures.- Chapter 6. Count-Based Regression Models.- Chapter 7. Multilevel Regression Models.- Chapter 8. Statistical Power.- Chapter 9. Special Topics: Randomized Experiments.- Chapter 10. Propensity Score Matching.- Chapter 11. Meta-Analysis.- Chapter 12. Spatial Regression.

Read more less

Book SynopsisThis case study-based textbook in multivariate analysis for advanced students in the humanities emphasizes descriptive, exploratory analyses of various types of datasets from a wide range of sub-disciplines, promoting the use of multivariate analysis and illustrating its wide applicability. Fields featured include, but are not limited to, historical agriculture, arts (music and painting), theology, and stylometrics (authorship issues). Most analyses are based on existing data, earlier analysed in published peer-reviewed papers.Four preliminary methodological and statistical chapters provide general technical background to the case studies. The multivariate statistical methods presented and illustrated include data inspection, several varieties of principal component analysis, correspondence analysis, multidimensional scaling, cluster analysis, regression analysis, discriminant analysis, and three-mode analysis.The bulk of the text is taken up by 14 case studies that lean heavily on graphical representations of statistical information such as biplots, using descriptive statistical techniques to support substantive conclusions. Each study features a description of the substantive background to the data, followed by discussion of appropriate multivariate techniques, and detailed results interpreted through graphical illustrations. Each study is concluded with a conceptual summary. Datasets in SPSS are included online.Table of Contents

Read more less

Book SynopsisThis open access book presents a ground-breaking approach to developing micro-foundations for demography and migration studies. It offers a unique and novel methodology for creating empirically grounded agent-based models of international migration – one of the most uncertain population processes and a top-priority policy area. The book discusses in detail the process of building a simulation model of migration, based on a population of intelligent, cognitive agents, their networks and institutions, all interacting with one another. The proposed model-based approach integrates behavioural and social theory with formal modelling, by embedding the interdisciplinary modelling process within a wider inductive framework based on the Bayesian statistical reasoning. Principles of uncertainty quantification are used to devise innovative computer-based simulations, and to learn about modelling the simulated individuals and the way they make decisions. The identified knowledge gaps are subsequently filled with information from dedicated laboratory experiments on cognitive aspects of human decision-making under uncertainty. In this way, the models are built iteratively, from the bottom up, filling an important epistemological gap in migration studies, and social sciences more broadly.Trade Review“The material collected by Jakub Bijak and his team constitutes a valuable resource for scholars interested in modelling individual decisions, not necessarily restricted to migration processes. … Researchers who already gained some experience in social simulation will receive many inspirations for improving their own research and rise to the next level. In this way, this book has the potential to advance the art of modelling in the social sciences.” (Thomas Fent, European Journal of Population, Vol. 38, 2022)Table of ContentsPart I: Preliminaries: Chapter 1. Introduction.- Chapter 2. Uncertainty and complexity: towards model-based demography.- Part II: Elements of the modelling process.- Chapter 3. Principles and state of the art of agent-based migration modelling.- Chapter 4. Building a knowledge base for the model.- Chapter 5. Uncertainty quantification, model calibration and sensitivity.- Chapter 6. The boundaries of cognition and decision making.- Chapter 7. Agent-based modelling and simulation with domain-specific languages.- Part III: Model results, applications, and reflections.- Chapter 8. Towards more realistic models.- Chapter 9. Bayesian model-based approach: impact on science and policy.- Chapter 10. Open science, replicability, and transparency in modelling.- Chapter 11. Conclusions: towards a Bayesian modelling process.

Read more less

Book SynopsisThis book introduces the fundamentals of research methods and how they apply to the discipline of urban and regional planning. Written at a level appropriate for upper-level undergraduate and beginning master’s level students, the text fills a gap in the literature for textbooks on urban planning. Additionally, the book can be used as a reference for planning practitioners and researchers when analyzing quantitative and qualitative data in urban and regional planning and related fields.The volume does not assume advanced knowledge of mathematical formulas. Rather, it begins with the essentials of research methods, such as the identification of the research problems in planning, the literature review, data collection and presentation, descriptive data analysis, and report of findings. Its discipline-specific topics include field research methods, qualitative data analysis, economic and demographic analysis, evaluation research, and methods in sub-disciplines such as land use planning, transportation planning, environmental planning, and housing analysis. Designed with instruction in mind, this book features downloadable materials, including learning outcomes, chapter highlights, chapter review questions, datasets, and certain Excel models. Students will be able to download review questions to enhance the learning process and datasets to practice methods.Table of Contents

Read more less

a huge range and FREE tracked UK delivery on ALL orders.

Read more less

Book Synopsis

Read more less

Book SynopsisThe Handbook is written for academics, researchers, practitioners and advanced graduate students. It has been designed to be read by those new or starting out in the field of spatial analysis as well as by those who are already familiar with the field. The chapters have been written in such a way that readers who are new to the field will gain important overview and insight. At the same time, those readers who are already practitioners in the field will gain through the advanced and/or updated tools and new materials and state-of-the-art developments included. This volume provides an accounting of the diversity of current and emergent approaches, not available elsewhere despite the many excellent journals and te- books that exist. Most of the chapters are original, some few are reprints from the Journal of Geographical Systems, Geographical Analysis, The Review of Regional Studies and Letters of Spatial and Resource Sciences. We let our contributors - velop, from their particular perspective and insights, their own strategies for m- ping the part of terrain for which they were responsible. As the chapters were submitted, we became the first consumers of the project we had initiated. We gained from depth, breadth and distinctiveness of our contributors’ insights and, in particular, the presence of links between them.Trade ReviewFrom the reviews:“The Handbook of Applied Spatial Analysis provides an important summary of, and gateway into, the rapidly developing field of spatial analysis. It aims to provide both a useful guide for researchers at all levels in spatial analytic fields and a basis for more in-depth research. … certainly fulfils the expectations set out in its blurb. It provides a thorough … insight into contemporary spatial analysis that many with an interest in this field will find useful.” (James Cheshire, Environment and Planning B: Planning and Design, Vol. 37, 2010)“It provides a comprehensive introduction to a variety of problems and methods that may be beneficial to students and researchers who intend to learn and apply spatial analysis techniques in their studies and/or research. More importantly, the book provides valuable breadth and depth in its treatment of many topics. … suitable for readers without substantial prior knowledge of spatial analysis. A book with such a combination of topics and qualities is a pleasant and valuable addition to the rich literature in this area.” (Changshan Wu, Journal of Regional Science, Vol. 52 (2), 2012)“The editors have done an excellent job to bring together conceptual knowledge and application pursuits while empowering readers with the information they need to find these resources and try some of the included techniques using the examples to guide them. The book will be attractive to higher level students and professionals … . There are not many books as up-to-date with such a wide coverage of spatial analysis tools and techniques along with supporting resource information.” (Jeff Thurston, Sensors & Systems, July, 2010)Table of ContentsGI Software Tools.- Spatial Statistics in ArcGIS.- Spatial Statistics in SAS.- Spatial Econometric Functions in R.- GeoDa: An Introduction to Spatial Data Analysis.- STARS: Space-Time Analysis of Regional Systems.- Space-Time Intelligence System Software for the Analysis of Complex Systems.- Geostatistical Software.- GeoSurveillance: GIS-based Exploratory Spatial Analysis Tools for Monitoring Spatial Patterns and Clusters.- Web-based Analytical Tools for the Exploration of Spatial Data.- PySAL: A Python Library of Spatial Analytical Methods.- Spatial Statistics and Geostatistics.- The Nature of Georeferenced Data.- Exploratory Spatial Data Analysis.- Spatial Autocorrelation.- Spatial Clustering.- Spatial Filtering.- The Variogram and Kriging.- Spatial Econometrics.- Spatial Econometric Models.- Spatial Panel Data Models.- Spatial Econometric Methods for Modeling Origin-Destination Flows.- Spatial Econometric Model Averaging.- Geographically Weighted Regression.- Expansion Method, Dependency, and Multimodeling.- Multilevel Modeling.- The Analysis of Remotely Sensed Data.- ARTMAP Neural Network Multisensor Fusion Model for Multiscale Land Cover Characterization.- Model Selection in Markov Random Fields for High Spatial Resolution Hyperspectral Data.- Geographic Object-based Image Change Analysis.- Applications in Economic Sciences.- The Impact of Human Capital on Regional Labor Productivity in Europe.- Income Distribution Dynamics and Cross-Region Convergence in Europe.- A Multi-Equation Spatial Econometric Model, with Application to EU Manufacturing Productivity Growth.- Applications in Environmental Sciences.- A Fuzzy -Means Classification and a Bayesian Approach for Spatial Prediction of Landslide Hazard.- Incorporating Spatial Autocorrelation in Species Distribution Models.- A Web-based Environmental Decision Support System for Environmental Planning and Watershed Management.- Applications in Health Sciences.- Spatio-Temporal Patterns of Viral Meningitis in Michigan, 1993 - 2001.- Space-Time Visualization and Analysis in the Cancer Atlas Viewer.- Exposure Assessment in Environmental Epidemiology.

Read more less

Book Synopsis

Read more less

Book SynopsisThis book addresses sample size and power in the context of research, offering valuable insights for graduate and doctoral students as well as researchers in any discipline where data is generated to investigate research questions. It explains how to enhance the authenticity of research by estimating the sample size and reporting the power of the tests used. Further, it discusses the issue of sample size determination in survey studies as well as in hypothesis testing experiments so that readers can grasp the concept of statistical errors, minimum detectable difference, effect size, one-tail and two-tail tests and the power of the test. The book also highlights the importance of fixing these boundary conditions in enhancing the authenticity of research findings and improving the chances of research papers being accepted by respected journals. Further, it explores the significance of sample size by showing the power achieved in selected doctoral studies. Procedure has been discussed to fix power in the hypothesis testing experiment. One should usually have power at least 0.8 in the study because having power less than this will have the issue of practical significance of findings. If the power in any study is less than 0.5 then it would be better to test the hypothesis by tossing a coin instead of organizing the experiment. It also discusses determining sample size and power using the freeware G*Power software, based on twenty-one examples using different analyses, like t-test, parametric and non-parametric correlations, multivariate regression, logistic regression, independent and repeated measures ANOVA, mixed design, MANOVA and chi-square.Table of ContentsPreface Acknowledgements 1 Introduction to Sample Size Determination Introduction Issue of Power due to inappropriate sample size Some case studies Flow Diagram of Determining sample size and power Summary 2 Understanding Statistical Inference Introduction Estimating Parameters Estimating Population Mean Confidence Coefficient Confidence Interval Factors Affecting Confidence Interval Estimating Population Proportion Hypothesis Testing Type I and Type II Errors Power of the Test Relationship between Type I and Type II Errors One Tailed and Two Tailed Tests Procedure in Hypothesis Testing Experiment Effect Size Summary 3 Understanding Concepts in Estimating Sample Size in Survey Studies Introduction Determining Sample Size in Estimating Population Mean Factors Affecting Sample Size Sample Size Determination for Estimating Mean when Population SD Known: Illustration 3.1 Sample Size Determination for Estimating Mean when Population SD Unknown: Illustration 3.2 Sample Size Determination for Estimating Mean when Population SD Unknown: Illustration 3.3 Sample Size Determination for Estimating Mean when Population SD Unknown: Illustration 3.4 Determining Sample Size in Estimating Population Proportion Sample Size Determination for Estimating Proportion: Illustration 3.5 Sample Size Determination for Estimating Proportion: Illustration 3.6 Sample Size Determination for Estimating Proportion: Illustration 3.7 Sample Size Determination for Estimating Proportion: Illustration 3.8 Determining Sample Size in Estimating Difference Between Two Population Means Summary 4 Understanding Concepts in Estimating Sample Size in Hypothesis Testing Experiment Introduction Sample Size on the Basis of Power One Sample Testing of Mean Determining Sample Size Estimation of Minimum Sample Size to Test H0 : µ=37 : Illustration 4.1 Minimum Detectable Difference Estimation of Minimum Detectable Difference for Testing H0: µ=37: Illustration 4.2 Estimation of Power in One Sample t Test Estimation of Power in Testing H0: µ=37: Illustration 4.3 Testing Difference Between Two Means Determining Sample Size in Two Sample t Test Estimation of Sample Size for Two Sample t Test for Mean : Illustration 4.4 Estimation of Power in Two Sample t Test Estimation of Power in Two Sample t Test for Mean : Illustration 4.5 Summary 5 Use of G*Power Software Introduction Procedure of Installing G*Power 3.1 Summary 6 Determining Sample Size in Experimental Studies Introduction One Sample Testing Testing Difference of Sample Mean from Population Mean Sample Size and Power Determination: Illustration 6.1 Testing Difference of Sample Proportion from Population Proportion Sample Size Determination: Illustration 6.2 Two Sample Testing Comparing Group Means in Two Independent Samples Sample Size and Power Determination: Illustration 6.3 Comparing Paired Group Means Sample Size Determination: Illustration 6.4 Comparing two Group Means Using Mann Whitney Test Sample Size Determination: Illustration 6.5 Comparing Paired Group Means Using Wilcoxon Signed Rank Test Sample Size Determination: Illustration 6.6 Comparing Two Proportions Sample Size Determination: Illustration 6.7 Correlation Coefficient: Testing Significance Case I: Testing Whether Sample Correlation Differs From 0 Sample Size Determination: Illustration 6.14 Case II: Testing Whether Sample Correlation Differs from a Known Value Sample Size Determination: Illustration 6.15 Correlation Coefficients: Testing Significant Difference Between Two Independent Correlations Sample Size Determination: Illustration 6.16 Bi-Serial Correlation: Testing Significance Sample Size Determination: Illustration 6.17 Goodness of Fit: Testing With Chi-Square Sample Size Determination in Goodness of Fit: Illustration 6.18 Linear Multiple Regression Model Sample Size Determination in Linear Multiple Regression: Illustration 6.19 Logistic Regression Sample Size Determination for Continuous Predictors: Illustration 6.20 Sample Size Determination for a Dichotomous Predictor: Illustration 6.21 Summary 7 Determining Sample Size in General Linear Models Introduction Analysis of Variance One–Way Analysis of Variance Sample Size Determination: Illustration 6.8 Two–Way Analysis of Variance Sample Size Determination for Main and Interaction Effect: Illustration 6.9 Repeated Measures ANOVA Between Factors Sample Size Determination: Illustration 6.10 Repeated Measures ANOVA Within Factors Sample Size Determination: Illustration 6.11 Repeated ANOVA Within-Between Interaction Manova Experiment: for Testing the Significance of Global Effect Sample Size Determination: Illustration 6.12 Manova Experiment: Testing Significance of Interaction Effect Sample Size Determination: Illustration 6.13 Summary Appendix Bibliography

Read more less

Book SynopsisContemporary Vulnerabilities offers critical reflections about vulnerable moments in research committed to social change. This interdisciplinary collection gathers reflexive narratives and analyses about innovative methodologies that engage with unconventional and unexpected research spaces inhabited and shared by scholars. The authors encourage us to collaborate within, reflect on, and confront the frictions of inquiry around social change. With an aim of contesting the dominance of Eurocentric epistemologies, the collection includes modes of storytelling and examples of knowledge gathering that are often excluded from academic texts in general and methodological texts in particular. All those interested in research methodologies and social justice inquiry will find provocation and recognition in this volume, including scholars, ethics boards, and students.Contributors: Aly Bailey, Kayla Besse, Meredith Bessey, Madeline Burghardt, Claire Carter, Shraddha Chatterjee, Yuriko Cowper-Smith, Eva Cupchik, Cheyanne Desnomie, Bongi Dube, Athanasia Francis, Rebecca Godderis, Moses Gordon, Emily Grafton, Caitlin Janzen, Evadne Kelly, Debra Langan, Rebecca Lennox, Corinne L. Mason, Tara-Leigh McHugh, Preeti Nayak, Anh Ngo, Jess Notwell, Marcia Oliver, Cassandra J. Opikokew Wajuntah, Merrick Pilling, Kendra-Ann Pitt, Salima Punjani, seeley quest, Carla Rice, Jen Rinaldi, Lori Ross, Kate Rossiter, Brenda Rossow-Kimball, Siobhán Saravanamuttu, Melissa Schnarr, Bettina Schneider, Irene Shankar, Skylar Sookpaiboon, Chelsea Temple Jones, Amelia Thorpe, Paul Tshuma, Amber-Lee Varadi, Jijian Voronka, Kristyn White.

Read more less

Book SynopsisHow do we make sense of Aotearoa New Zealand's diverse and changing society? This book introduces readers to the range of theories, approaches and techniques that we will need to understand this country in the twenty-first century. Part one, `the big picture', looks at how different cultures gather knowledge, introducing readers to science, social science, Maori approaches, cross-cultural and feminist research, and ethics. Part two, `the basics of social science research', explains how to do a literature review, design a research project, collect and analyse quantitative and qualitative data, and write up the results. In part three, `techniques of social research', a number of prominent New Zealand social scientists show how research really gets done by explaining the use of key techniques in their own research projects, from official statistics and longitudinal research to focus groups and ethnography. This is a book for New Zealand students and practitioners written by New Zealand social scientists, highlighting what is different about doing research in this country in the twenty-first century. The book is as much about qualitative approaches as quantitative ones and introduces readers to the practice of research through real cases, rather than just theory. The editors are fierce methodological pluralists, and they introduce the wide range of tools and approaches available to the modern researcher. For anyone coming to the many paths of social research for the first time, Social Science Research in New Zealand is the perfect introduction.

Read more less

Book Synopsis

Read more less

Book SynopsisRecently, social science has had numerous episodes of influential research that was found invalid when placed under rigorous scrutiny. The growing sense that many published results are potentially erroneous has made those conducting social science research more determined to ensure the underlying research is sound.Transparent and Reproducible Social Science Research is the first book to summarize and synthesize new approaches to combat false positives and non-reproducible findings in social science research, document the underlying problems in research practices, and teach a new generation of students and scholars how to overcome them. Understanding that social science research has real consequences for individuals when used by professionals in public policy, health, law enforcement, and other fields, the book crystallizes new insights, practices, and methods that help ensure greater research transparency, openness, and reproducibility. Readers are guided through well-known problems anTrade Review"Reminds us to, occasionally, take a moment for self-reflection to question what we are doing as individual researchers or as a scientific community and whether we should overcome certain habits to get better at our job of explaining the world around us." * Politics and the Life Sciences *Table of ContentsList of Figures List of Tables Acknowledgments PART ONE. INTRODUCTION AND MOTIVATION 1 Introduction 2 What Is Ethical Research? PART TWO. PROBLEMS 3 Publication Bias 4 Specification Searching PART THREE. SOLUTIONS 5 Using All Evidence: Registration and Meta-analysis 6 Pre-analysis Plans 7 Sensitivity Analysis and Other Approaches PART FOUR. PRACTICES 8 Reporting Standards 9 Replication 10 Data Sharing 11 Reproducible Workflow 12 Conclusion Appendix Bibliography Index

Read more less

Book SynopsisA free ebook version of this title is available through Luminos, University of California Press's Open Access publishing program. Visit www.luminosoa.org to learn more. This book explores analytic induction, an approach to the analysis of cross-case evidence on qualitative outcomes that has deep roots in sociology. A popular research technique in the early decades of empirical sociology, analytic induction differs fundamentally as a method of social research from conventional variation-based approaches. In Analytic Induction for Social Research, Charles C. Ragin demonstrates that much is gained from systematizing analytic induction. The approach he introduces here offers a new template for conducting cross-case analysis and provides a new set of tools for answering common research questions that existing methods cannot address.Table of ContentsContents Acknowledgments Introduction PART ONE. THE LOGIC OF ANALYTIC INDUCTION 1. Classic Analytic Induction 2. Reconciling Disconfirming Cases 3. Explaining Variation versus Explaining Outcomes 4. The Uses of “Negative” Cases in Social Research PART TWO. GENERALIZED ANALYTIC INDUCTION 5. Classic versus Generalized Analytic Induction 6. The Interpretive Logic of Generalized Analytic Induction 7. Generalized Analytic Induction: A Step-by-Step Guide 8. Using Generalized AI to Reanalyze Viterna’s Study of Women’s Mobilization into the Salvadoran Guerrilla Army 9. Applying Generalized AI to Conventional Quantitative Data 10. Core Features of Generalized Analytic Induction Appendix A. Brief Overview of Qualitative Comparative Analysis Appendix B. Fuzzy Sets Appendix C. Using fsQCA Software to Implement Generalized AI Appendix D. Converting “Sum-of-Products” Expressions to “Product-of-Sums” Expressions Appendix E. Measures Used in Logistic Regression Analysis Notes References Index

Read more less

Book SynopsisCo-authored by an international team of experts across disciplines, this important book is one of the first to demonstrate the enormous benefit creative methods offer for education research. It illustrates how using creative methods, such as poetic inquiry, theatre and animation, can support learning and illuminate participation and engagement.Table of ContentsIntroduction Research Design Context-Setting Data Gathering Using Two Dimensional and Technological Methods – Research With Children and Young People Data Gathering Using Three Dimensional and Online Methods – Research With Adults Data Analysis Writing/Reporting Presentation Dissemination Where to Next With Creative Research Methods

Read more less

Book SynopsisIn Anthropology in the Meantime Michael M. J. Fischer draws on his real world, multi-causal, multi-scale, and multi-locale research to rebuild theory for the twenty-first century. Providing a history and inventory of experimental methods and frameworks in anthropology from the 1920s to the present, Fischer presents anthropology in the meantime as a methodological injunction to do ethnography that examines how the pieces of the world interact, fit together or clash, generate complex unforeseen consequences, reinforce cultural references, and cause social ruptures. Anthropology in the meantime requires patience, constant experimentation, collaboration, the sounding-out of affects and nonverbal communication, and the conducting of ethnographically situated research over longitudinal time. Perhaps above all, anthropology in the meantime is no longer anthropology of and about peoples; it is written with and for the people who are its subjects. Anthropology in the MeantTrade Review"Anthropology in the Meantime is a rich collection of essays in tune with the central debates in contemporary cultural anthropology. . . . It serves as a survey of the present state of the field, identifying the tensions and re-inscribing them in the long tradition of anthropological scholarship. . . . Recommended. Advanced undergraduates and above." -- A. Ponce de Leon * Choice *" [This book] maintains a productive line that brings one back to the spirit, above all, of ethnographic exploration as idea and method mining. ... I believe it arrives at a perfect moment. [Fischer] contributes to various contemporary discussions within anthropology on religion, film, politics, postcolonialism, and gender/sexuality." -- Joseph Russo * Anthropological Quarterly *“This wonderful and well-researched collection of essays on third ethnographic spaces offers a pragmatic vision for anthropology in the Kantian spirit of the formation of a world society. A must read indeed in times of rapid change.” -- Michelangelo Paganopoulos * Journal of the Royal Anthropological Institute *Table of ContentsPrologue: Changing Modes of Ethnographic Authority 1 Part I. Ethnography in the Meantime 1. Experimental Ethnography in Ink, Light, Sound, and Performance 39 2. Ontology and Metaphysics Are False Leads 49 3. Pure Logic and Typologizing Are False Leads 79 Part II. Ground-Truthing 4. Violence and Deep Play 99 5. Amazonian Ethnography and the Politics of Renewal 114 6. Ethnic Violence, Galactic Polities, and the Great Transformation 130 Part III. Tone and Tuning 7. Health Care in India 161 8. Hospitality 186 9. Anthropology and Philosophy 198 Part IV. Temporalities and Recursivities 10. Changing Media of Ethnographic Writing 233 11. Recalling Writing Culture 258 12. Anthropological Modes of Concern 276 Epilogue: Third Spaces and Ethnography in the Anthropocene 298 Acknowledgments 345 Notes 349 Bibliography 391 Index 429

Read more less

Book SynopsisThinking with Theory in Qualitative Research: Second Edition demonstrates how to enact various philosophical concepts in practices of inquiry, effectively opening up the process of thought in qualitative studies.Thinking with Theory in Qualitative Research functions as a refusal of pregiven method, intensifying creativity, experimentation, and newness. Readers are invited into the threshold of theory to traverse philosophers and their concepts, reorienting conventional approaches to inquiry. Each chapter presents a thinking with process as a way of reading intensively through plugging in performative accounts of two first-generation academic women to philosophical concepts from Derrida, Spivak, Foucault, Butler, Barad, and Deleuze and Guattari. This book is a deliberate attempt to unsettle what is expected to be represented or recognized in terms of both meaning and method in traditional practices of qualitative research, which become unproductive and untTable of Contents1. Plugging One Text into Another, Interlude I: Why Derrida?, 2. Derrida: Thinking with Deconstruction, Interlude II: Why Spivak?, 3. Spivak: Thinking with Marginality, Interlude III: Why Foucault?, 4. Foucault: Thinking with Power/Knowledge, Interlude IV: Why Butler?, 5. Butler: Thinking with Performativity, Interlude V: Why Barad?, 6. Barad: Thinking with Intra-action, Interlude VI: Why Deleuze & Guattari?, 7. Deleuze and Guattari: Thinking with Desire, 8. Ontological writing: Unleashing Becomings and Worldings

Read more less

Book SynopsisA history of the Frankfurt School and its impact during its early years in Germany and the United States. This edition includes a new preface which reflects on the continuing relevance of the work of the Frankfurt School.Table of ContentsPreface to the 1996 Edition Foreword by Max Horkheimer Introduction Acknowledgments I. The Creation of the Institut fUr Sozialforschung and Its First Frankfurt Years 2. The Genesis of Critical Theory 3· The Integration of Psychoanalysis 4. The Institut's First Studies of Authority 5. The Institut's Analysis of Nazism 6. Aesthetic Theory and the Critique of Mass Culture 7· The Empirical Work of the Institut in the 1940's 8. Toward a Philosophy of History: The Critique of the Enlightenment Epilogue Chapter References Bibliography Index

Read more less

Book SynopsisComputing power has revolutionized the theory and practice of statistical inference. This book delivers a concentrated course in modern statistical thinking by tracking the revolution from classical theories to the large-scale prediction algorithms of today. Anyone who applies statistical methods to data will benefit from this landmark text.Trade Review'How and why is computational statistics taking over the world? In this serious work of synthesis that is also fun to read, Efron and Hastie, two pioneers in the integration of parametric and nonparametric statistical ideas, give their take on the unreasonable effectiveness of statistics and machine learning in the context of a series of clear, historically informed examples.' Andrew Gelman, Columbia University, New York'This unusual book describes the nature of statistics by displaying multiple examples of the way the field has evolved over the past sixty years, as it has adapted to the rapid increase in available computing power. The authors' perspective is summarized nicely when they say, 'very roughly speaking, algorithms are what statisticians do, while inference says why they do them'. The book explains this 'why'; that is, it explains the purpose and progress of statistical research through a close look at many major methods, methods the authors themselves have advanced and studied at great length. Both enjoyable and enlightening, Computer Age Statistical Inference is written especially for those who want to hear the big ideas, and see them instantiated through the essential mathematics that defines statistical analysis. It makes a great supplement to the traditional curricula for beginning graduate students.' Rob Kass, Carnegie Mellon University, Pennsylvania'This is a terrific book. It gives a clear, accessible, and entertaining account of the interplay between theory and methodological development that has driven statistics in the computer age. The authors succeed brilliantly in locating contemporary algorithmic methodologies for analysis of 'big data' within the framework of established statistical theory.' Alastair Young, Imperial College London'This is a guided tour of modern statistics that emphasizes the conceptual and computational advances of the last century. Authored by two masters of the field, it offers just the right mix of mathematical analysis and insightful commentary.' Hal Varian, Google'Efron and Hastie guide us through the maze of breakthrough statistical methodologies following the computing evolution: why they were developed, their properties, and how they are used. Highlighting their origins, the book helps us understand each method's roles in inference and/or prediction. The inference-prediction distinction maintained throughout the book is a welcome and important novelty in the landscape of statistics books.' Galit Shmueli, National Tsing Hua University'A masterful guide to how the inferential bases of classical statistics can provide a principled disciplinary frame for the data science of the twenty-first century.' Stephen Stigler, University of Chicago, and author of Seven Pillars of Statistical Wisdom'Computer Age Statistical Inference offers a refreshing view of modern statistics. Algorithmics are put on equal footing with intuition, properties, and the abstract arguments behind them. The methods covered are indispensable to practicing statistical analysts in today's big data and big computing landscape.' Robert Gramacy, University of Chicago Booth School of Business'Every aspiring data scientist should carefully study this book, use it as a reference, and carry it with them everywhere. The presentation through the two-and-a-half-century history of statistical inference provides insight into the development of the discipline, putting data science in its historical place.' Mark Girolami, Imperial College London'Efron and Hastie are two immensely talented and accomplished scholars who have managed to brilliantly weave the fiber of 250 years of statistical inference into the more recent historical mechanization of computing. This book provides the reader with a mid-level overview of the last 60-some years by detailing the nuances of a statistical community that, historically, has been self-segregated into camps of Bayes, frequentist, and Fisher yet in more recent years has been unified by advances in computing. What is left to be explored is the emergence of, and role that, big data theory will have in bridging the gap between data science and statistical methodology. Whatever the outcome, the authors provide a vision of high-speed computing having tremendous potential to enable the contributions of statistical inference toward methodologies that address both global and societal issues.' Rebecca Doerge, Carnegie Mellon University, Pennsylvania'In this book, two masters of modern statistics give an insightful tour of the intertwined worlds of statistics and computation. Through a series of important topics, Efron and Hastie illuminate how modern methods for predicting and understanding data are rooted in both statistical and computational thinking. They show how the rise of computational power has transformed traditional methods and questions, and how it has pointed us to new ways of thinking about statistics.' David Blei, Columbia University, New York'Absolutely brilliant. This beautifully written compendium reviews many big statistical ideas, including the authors' own. A must for anyone engaged creatively in statistics and the data sciences, for repeated use. Efron and Hastie demonstrate the ever-growing power of statistical reasoning, past, present, and future.' Carl Morris, Harvard University, Massachusetts'Computer Age Statistical Inference gives a lucid guide to modern statistical inference for estimation, hypothesis testing, and prediction. The book seamlessly integrates statistical thinking with computational thinking, while covering a broad range of powerful algorithms for learning from data. It is extraordinarily rare and valuable to have such a unified treatment of classical (and classic) statistical ideas and recent 'big data' and machine learning ideas. Accessible real-world examples and insightful remarks can be found throughout the book.' Joseph K. Blitzstein, Harvard University, Massachusetts'Among other things, it is an attempt to characterize the current state of statistics by identifying important tools in the context of their historical development. It also offers an enlightening series of illustrations of the interplay between computation and inference … This is an attractive book that invites browsing by anyone interested in statistics and its future directions.' Bill Satzer, Mathematical Association of America Reviews'My take on Computer Age Statistical Inference is that experienced statisticians will find it helpful to have such a compact summary of twentieth-century statistics, even if they occasionally disagree with the book's emphasis; students beginning the study of statistics will value the book as a guide to statistical inference that may offset the dangerously mind-numbing experience offered by most introductory statistics textbooks; and the rest of us non-experts interested in the details will enjoy hundreds of hours of pleasurable reading.' Joseph Rickert, RStudio (www.rstudio.com)'Efron and Hastie (both, Stanford Univ.) have superbly crafted a central text/reference book that presents a broad overview of modern statistics. The work examines major developments in computation from the late-20th and early-21st centuries, ranging from electronic computations to 'big data' analysis. Focusing primarily on the last six decades, the text thoroughly documents the progression within the discipline of statistics … This text is highly recommended for graduate libraries.' D. J. Gougeon, ChoiceTable of ContentsPart I. Classic Statistical Inference: 1. Algorithms and inference; 2. Frequentist inference; 3. Bayesian inference; 4. Fisherian inference and maximum likelihood estimation; 5. Parametric models and exponential families; Part II. Early Computer-Age Methods: 6. Empirical Bayes; 7. James–Stein estimation and ridge regression; 8. Generalized linear models and regression trees; 9. Survival analysis and the EM algorithm; 10. The jackknife and the bootstrap; 11. Bootstrap confidence intervals; 12. Cross-validation and Cp estimates of prediction error; 13. Objective Bayes inference and Markov chain Monte Carlo; 14. Statistical inference and methodology in the postwar era; Part III. Twenty-First Century Topics: 15. Large-scale hypothesis testing and false discovery rates; 16. Sparse modeling and the lasso; 17. Random forests and boosting; 18. Neural networks and deep learning; 19. Support-vector machines and kernel methods; 20. Inference after model selection; 21. Empirical Bayes estimation strategies; Epilogue; References; Index.

Read more less

Book SynopsisNew Third Edition! If sociology could teach everyone just one thing, what would it be? The Forest and the Trees is one sociologist's response to the hypothetical-the core insight with the greatest potential to change how people see the world and themselves in relation to it. This Third Edition features: Updated key references, data, resources, and examples, from global warming, Obama's election, and gay marriage to transgender/cisgender and the Occupy Movement A glossary of terms The short essays in Chapter 6, framed around the power of sociology, dig beneath easy and popular understandings to reveal what lies beneath An additional analysis of how men's violence is made invisible even though most violence is perpetrated by men Chapter 7's focus on sociology as a worldview with an analysis of the origins of white privilegeTrade Review"There is no better book to help college students understand the sociological mindset."-Terence J. McGinn, The University of Michigan"I love The Forest and the Trees. And, honestly, if there was not a new edition, I am not sure how I would teach my introduction to sociology course. My students often comment that it was the best book in a class they have ever read. I cannot sing the praises of The Forest and the Trees enough!"-Marisol Clark-Ibáñez, Associate Professor of Sociology, California State University, San MarcosTable of ContentsAcknowledgments Introduction: Life, Practice, and Promise 1 The Forest, the Trees, and the One Thing 2 Culture: Symbols, Ideas, and the Stuff of Life 3 The Structures of Social Life 4 Population and Human Ecology: People, Space, and Place 5 Us, It, and Social Interaction 6 Things Are Not What They Seem 7 Sociology as Worldview: Where White Privilege Came From Epilogue: Who Are We Really? Notes Glossary Index

Read more less

Book SynopsisKeeping the uniquely humorous and self-deprecating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world. The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual undeTrade ReviewIn statistics, R is the way of the future. The big boys and girls have known this for some time: There are now millions of R users in academia and industry. R is free (as in no cost) and free (as in speech). Andy, Jeremy, and Zoe′s book now makes R accessible to the little boys and girls like me and my students. Soon all classes in statistics will be taught in R. I have been teaching R to psychologists for several years and so I have been waiting for this book for some time. The book is excellent, and it is now the course text for all my statistics classes. I′m pretty sure the book provides all you need to go from statistical novice to working researcher. Take, for example, the chapter on t-tests. The chapter explains how to compare the means of two groups from scratch. It explains the logic behind the tests, it explains how to do the tests in R with a complete worked example, which papers to read in the unlikely event you do need to go further, and it explains what you need to write in your practical report or paper. But it also goes further, and explains how t-tests and regression are related---and are really the same thing---as part of the general linear model. So this book offers not just the step-by-step guidance needed to complete a particular test, but it also offers the chance to reach the zen state of total statistical understanding. Prof. Neil StewartWarwick University Field′s Discovering Statistics is popular with students for making a sometimes deemed inaccessible topic accessible, in a fun way. In Discovering Statistics Using R, the authors have managed to do this using a statistics package that is known to be powerful, but sometimes deemed just as inaccessible to the uninitiated, all the while staying true to Field′s off-kilter approach. Dr Marcel van Egmond University of Amsterdam Probably the wittiest and most amusing of the lot (no, really), this book takes yet another approach: it is 958 pages of R-based stats wisdom (plus online accoutrements)... A thoroughly engaging, expansive, thoughtful and complete guide to modern statistics. Self-deprecating stories lighten the tone, and the undergrad-orientated ′stupid faces′ (Brian Haemorrhage, Jane Superbrain, Oliver Twisted, etc.) soon stop feeling like a gimmick, and help to break up the text with useful snippets of stats wisdom. It is very mch a student textbook but it is brilliant... Field et al. is the complete package.David M. Shuker AnimJournal of Animal Behaviour "This work should be in the library of every institution where statistics is taught. It contains much more content than what is required for a beginning or advanced undergraduate course, but instructors for such courses would do well to consider this book; it is priced comparably to books which contain only basic material, and students who are fascinated by the subject may find the additional material a real bonus. The book would also be very good for self-study. Overall, an excellent resource." -- R. Bharath * Choice *The main strength of this book is that it presents a lot of information in an accessible, engaging and irreverent way. The style is informal with interesting excursions into the history of statistics and psychology. There is reference to research papers which illustrate the methods explained, and are also very entertaining. The authors manage to pull off the Herculean task of teaching statistics through the medium of R... All in all, an invaluable resource. -- Paul WebbTable of ContentsWhy Is My Evil Lecturer Forcing Me to Learn Statistics? What will this chapter tell me? What the hell am I doing here? I don′t belong here Initial observation: finding something that needs explaining Generating theories and testing them Data collection 1: what to measure Data collection 2: how to measure Analysing data What have I discovered about statistics? Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Everything You Ever Wanted to Know About Statistics (Well, Sort of) What will this chapter tell me? Building statistical models Populations and samples Simple statistical models Going beyond the data Using statistical models to test research questions What have I discovered about statistics? Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research The R Environment What will this chapter tell me? Before you start Getting started Using R Getting data into R Entering data with R Commander Using other software to enter and edit data Saving Data Manipulating Data What have I discovered about statistics? R Packages Used in This Chapter R Functions Used in This Chapter Key terms that I′ve discovered Smart Alex′s Tasks Further reading Exploring Data with Graphs What will this chapter tell me? The art of presenting data Packages used in this chapter Introducing ggplot2 Graphing relationships: the scatterplot Histograms: a good way to spot obvious problems Boxplots (box-whisker diagrams) Density plots Graphing means Themes and options What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Exploring Assumptions What will this chapter tell me? What are assumptions? Assumptions of parametric data Packages used in this chapter The assumption of normality Testing whether a distribution is normal Testing for homogeneity of variance Correcting problems in the data What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Correlation What will this chapter tell me? Looking at relationships How do we measure relationships? Data entry for correlation analysis Bivariate correlation Partial correlation Comparing correlations Calculating the effect size How to report correlation coefficents What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Regression What will this chapter tell me? An Introduction to regression Packages used in this chapter General procedure for regression in R Interpreting a simple regression Multiple regression: the basics How accurate is my regression model? How to do multiple regression using R Commander and R Testing the accuracy of your regression model Robust regression: bootstrapping How to report multiple regression Categorical predictors and multiple regression What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Logistic Regression What will this chapter tell me? Background to logistic regression What are the principles behind logistic regression? Assumptions and things that can go wrong Packages used in this chapter Binary logistic regression: an example that will make you feel eel How to report logistic regression Testing assumptions: another example Predicting several categories: multinomial logistic regression What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Comparing Two Means What will this chapter tell me? Packages used in this chapter Looking at differences The t-test The independent t-test The dependent t-test Between groups or repeated measures? What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Comparing Several Means: ANOVA (GLM 1) What will this chapter tell me? The theory behind ANOVA Assumptions of ANOVA Planned contrasts Post hoc procedures One-way ANOVA using R Calculating the effect size Reporting results from one-way independent ANOVA What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Analysis of Covariance, ANCOVA (GLM 2) What will this chapter tell me? What is ANCOVA? Assumptions and issues in ANCOVA ANCOVA using R Robust ANCOVA Calculating the effect size Reporting results What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Factorial ANOVA (GLM 3) What will this chapter tell me? Theory of factorial ANOVA (independant design) Factorial ANOVA as regression Two-Way ANOVA: Behind the scenes Factorial ANOVA using R Interpreting interaction graphs Robust factorial ANOVA Calculating effect sizes Reporting the results of two-way ANOVA What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Repeated-Measures Designs (GLM 4) What will this chapter tell me? Introduction to repeated-measures designs Theory of one-way repeated-measures ANOVA One-way repeated measures designs using R Effect sizes for repeated measures designs Reporting one-way repeated measures designs Factorisal repeated measures designs Effect Sizes for factorial repeated measures designs Reporting the results from factorial repeated measures designs What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Mixed Designs (GLM 5) What will this chapter tell me? Mixed designs What do men and women look for in a partner? Entering and exploring your data Mixed ANOVA Mixed designs as a GLM Calculating effect sizes Reporting the results of mixed ANOVA Robust analysis for mixed designs What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Non-Parametric Tests What will this chapter tell me? When to use non-parametric tests Packages used in this chapter Comparing two independent conditions: the Wilcoxon rank-sum test Comparing two related conditions: the Wilcoxon signed-rank test Differences between several independent groups: the Kruskal-Wallis test Differences between several related groups: Friedman′s ANOVA What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Multivariate Analysis of Variance (MANOVA) What will this chapter tell me? When to use MANOVA Introduction: similarities and differences to ANOVA Theory of MANOVA Practical issues when conducting MANOVA MANOVA using R Robust MANOVA Reporting results from MANOVA Following up MANOVA with discriminant analysis Reporting results from discriminant analysis Some final remarks What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Exploratory Factor Analysis What will this chapter tell me? When to use factor analysis Factors Research example Running the analysis with R Commander Running the analysis with R Factor scores How to report factor analysis Reliability analysis Reporting reliability analysis What have I discovered about statistics? R Packages Used in This Chapter R Functions Used in This Chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Categorical Data What will this chapter tell me? Packages used in this chapter Analysing categorical data Theory of Analysing Categorical Data Assumptions of the chi-square test Doing the chi-square test using R Several categorical variables: loglinear analysis Assumptions in loglinear analysis Loglinear analysis using R Following up loglinear analysis Effect sizes in loglinear analysis Reporting the results of loglinear analysis What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Multilevel Linear Models What will this chapter tell me? Hierarchical data Theory of multilevel linear models The multilevel model Some practical issues Multilevel modelling on R Growth models How to report a multilevel model What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Epilogue: Life After Discovering Statistics Troubleshooting R Glossary Appendix Table of the standard normal distribution Critical Values of the t-Distribution Critical Values of the F-Distribution Critical Values of the chi-square Distribution References

Read more less

Book SynopsisIn the social sciences today, students are taught theory by reading and analyzing the works of Karl Marx, Max Weber, and other foundational figures of the discipline. What they rarely learn, however, is how to actually theorize. The Art of Social Theory is a practical guide to doing just that. In this one-of-a-kind user's manual for social theorisTrade Review"[C]oncise and readable... Writing in accessible language and using the canon of social theorists to illustrate points, Swedberg meets a need for practitioners and students alike."--ChoiceTable of ContentsIntroduction: Why Theorize and Can You Learn to Do It? 1 Part 1: How to Theorize Chapter 1. Starting Anew 13 Chapter 2. Social Observation 29 Chapter 3. Naming, Concept, and Typology 52 Chapter 4. Analogy, Metaphor, and Pattern 80 Chapter 5. Coming Up with an Explanation 98 Part 2: Preparing for Theorizing Chapter 6. Heuristics 127 Chapter 7. Practical Exercises 146 Chapter 8. The Role of Theory 169 Chapter 9. Imagination and Art 188 Chapter 10. Summary and More 210 Appendix: How to Theorize according to Charles S. Peirce 230 Acknowledgments 249 Notes 251 References 253 Index 279

Read more less

Book Synopsis"The book has wide appeal in that the issues investigated - for example, the nature of science, practical work, the role of language, of technology and formative and summative assessment - are relevant and pertinent to science teachers' work in all school systems."Professor David F Treagust, Curtin University of Technology, AustraliaThis new edition of Good Practice in Science Teaching offers a comprehensive overview of the major areas of research and scholarship in science education.Each chapter summarizes the research work and evidence in the field, and discusses its significance, reliability and implications for the practice of science teaching.Thoroughly revised throughout, the new edition includes: Three new chapters covering: the learning of science in informal contexts; teacher professional development; and technology-mediated learning Updates to every chapter, reflecting the changes and developments in science education Further reTable of ContentsIntroduction: Research matters?Science teachers, science teaching: Issues and challenges How science works: What is the nature of scientific reasoning and what do we know about students' understanding? Science for citizenship Thinking about learning: Learning in science Science teaching and cognitive acceleration Practical work The role of language in the learning and teaching of science Technology mediated learning Formative assessment in science Summative assessment: Gold or glitter? Students' attitudes to science Supporting science learning in out-of-school contexts Supporting the development of effective science teachers Index

Read more less

Book SynopsisThis textbook provides a clear, concise, and comprehensive introduction to methodological issues encountered by the various social science disciplines. It emphasizes applications, with detailed examples, so that readers can put these methods to work in their research. Within a unified framework, John Gerring and Dino Christenson integrate a variety of methods - descriptive and causal, observational and experimental, qualitative and quantitative. The text covers a wide range of topics including research design, data-gathering techniques, statistics, theoretical frameworks, and social science writing. It is designed both for those attempting to make sense of social science, as well as those aiming to conduct original research. The text is accompanied by online practice questions, exercises, examples, and additional resources, including related readings and websites. An essential resource for undergraduate and postgraduate programs in communications, criminal justice, economics, business,Trade Review'An excellent guide to the main approaches and issues of social science research design. It offers a clear guide through the thicket of terms and concepts with effective use of examples. A valuable work for students of any level.' Kenneth Benoit, London School of Economics and Political Science'Rich, compelling, engaging, passionate and in crystal-clear style. Gerring and Christenson have done an excellent job in promoting an integrated and pluralist vision of methodology and research design.' Martino Maggetti, University of Lausanne, SwitzerlandTable of ContentsPreface; Part I. Building Blocks: 1. A unified framework; 2. Arguments; 3. Concepts and measures; 4. Analyses; Part II. Causality: 5. Causal frameworks; 6. Causal hypotheses and analyses; 7. Experimental designs; 8. Large-N observational designs; 9. Case study designs; 10. Diverse tools of causal inference; Part III. Process and Presentation: 11. Reading and reviewing; 12. Brainstorming; 13. Data gathering; 14. Writing; 15. Speaking; 16. Ethics; Part IV. Statistics: 17. Data management; 18. Univariate statistics; 19. Probability distributions; 20. Statistical inference; 21. Bivariate statistics; 22. Regression; 23. Causal inference; 24. Appendix; References; Index.

Read more less

Book SynopsisFrom the bestselling author of the acclaimed Chaos and Genius comes a thoughtful and provocative exploration of the big ideas of the modern era: Information, communication, and information theory.   Acclaimed science writer James Gleick presents an eye-opening vision of how our relationship to information has transformed the very nature of human consciousness. A fascinating intellectual journey through the history of communication and information, from the language of Africa’s talking drums to the invention of written alphabets; from the electronic transmission of code to the origins of information theory, into the new information age and the current deluge of news, tweets, images, and blogs. Along the way, Gleick profiles key innovators, including Charles Babbage, Ada Lovelace, Samuel Morse, and Claude Shannon, and reveals how our understanding of information is transforming not only how we look at the world, but how we live.A

Read more less

Book SynopsisReal world research is a common responsibility of professionals and practitioners in a wide range of both public and private settings. These include teachers, social workers and health service professionals, managers and specialists in business, architects, designers, criminologists and accountants among many others. Real World Research provides a clear route-map of the various steps needed to carry out a piece of applied research to a high professional standard. It is accessible to those without a social science background while providing rigorous and fully up-to-date coverage of contemporary issues and debates. It brings together materials and approaches from different social science disciplines, seeing value in both quantitative and qualitative approaches, as well as their combination in mixed-method designs. Updated throughout, the third edition includes: A brand new chapter on multi-strategy designs Increased covTable of ContentsPreface. Acknowledgements. Ways of using the book. The main steps when carrying out a project. PART I SETTING THE SCENE. Keeping a research journal. Chapter 1 Introduction. What is real world research? Design matters. Evaluation and change. The audience for this book. Returning to the real world. Beginning the journey. Chapter 2 Approaches to Social Research. Introduction. Postmodernism and extreme relativist approaches. The two traditions: quantitative and qualitative social research. The quantitative paradigm. The qualitative paradigm. Paradigms and research questions. A pragmatic approach. Multi-strategy research designs. Realism and real world research. The purposes of research. Practical value of the theoretical material covered in the chapter. PART II PLANNING: SELECTING A STRATEGY. Chapter 3 Developing Your Ideas. Introduction. Deciding on the focus. Searching and reviewing the literature. Research questions. Developing your research question(s). The place of theory. Chapter 4 General Design Issues. Introduction. A framework for research design. Getting a feel for design issues. Choosing a research design strategy. Establishing trustworthiness. Chapter 5 Fixed Designs. Introduction. General features of fixed designs. Establishing trustworthiness in fixed design research. Experimental fixed designs. True experiments. Quasi-experiments. Single-case experiments. Non-experimental fixed designs. Sample size in fixed designs. Chapter 6 Flexible Designs. Introduction. General features of flexible designs. Research traditions in qualitative research. Case studies. Ethnographic studies. Grounded theory studies. Other traditions. Sampling in flexible designs. Establishing trustworthiness in flexible design research. Chapter 7 Multi-strategy (Mixed Method) Designs. Introduction. The quantitative–qualitative incompatibility thesis. The mixed methods movement. Types of multi-strategy designs. Designing and carrying out multi-strategy research. Pragmatism, realism or 'anything goes'? Dealing with discrepancies in findings. Chapter 8 Designs for Particular Purposes: Evaluation, Action and Change. Introduction. Evaluation research. Action research. Intervention and change. Researchers and practitioners. Chapter 9 Ethical and Political Considerations. Introduction. Ethical codes and guidelines. Ethical issues. Researcher safety and risk. Working with vulnerable groups. General ethical responsibilities. Ethical review boards and committees. Politics and real world research. Sexism and social research. PART III TACTICS: THE METHODS OF DATA COLLECTION. Selecting the method(s). Chapter 10 Surveys and Questionnaires. Introduction. Designing surveys. Carrying out a sample survey. Designing and using a questionnaire. Diaries. Sampling in surveys – and elsewhere. Probability samples. Non-probability samples. Chapter 11 Interviews and Focus Groups. Introduction. Types and styles of interviews. General advice for interviewers. Content of the interview. Carrying out different types of interview. Focus groups. Dealing with interview data. Skills in interviewing. Chapter 12 Tests and Scales. Introduction. Measurement scales. Other scaling techniques. Using existing tests and scales. Developing your own test. Chapter 13 Observational Methods. Introduction. Observation in real world research. Approaches to observation. Participant observation. Getting started as a participant observer. Structured observation. Deciding on a coding scheme. The use of existing coding schemes. Developing your own scheme. Coding sequences of behaviour. Reliability and structured observation. Chapter 14 Additional Methods of Data Collection. Introduction. Unobtrusive measures. Content analysis of documents. Secondary data analysis. Introduction to a range of more specialist techniques. Internet-based research. Feminist research methods. Using multiple methods. Chapter 15 Writing a Project Proposal. Introduction. How to recognize a good proposal. The content of a research proposal. The problem of pre-specifying flexible design studies. Shortcomings of unsuccessful proposals. Sources of funding. PART IV CARRYING OUT THE PROJECT: ARRANGING THE PRACTICALITIES. Know what you are doing before starting the data collection. Negotiating access. Get yourself organized. Pilot if at all possible. Work on your relationships. Don't just disappear at the end. Don't expect it to work out as you planned. PART V DEALING WITH THE DATA. Collecting the data. Analysing and interpreting data. Realist analysis and interpretation. Preparing for analysis. Analysis or interpretation? Quantitative and qualitative data – and their integration in multi-strategy designs. Chapter 16 The Analysis and Interpretation of Quantitative Data. Introduction. Creating a data set. Starting data analysis. Exploring the data set. Exploring relationships between two variables. Exploring relationships among three or more variables. Analysing differences. Quantitative analysis and different fixed design research strategies. Chapter 17 The Analysis and Interpretation of Qualitative Data. Introduction. Types of qualitative analysis. Using the computer for qualitative data analysis. Dealing with the quantity of qualitative data. Thematic coding analysis. Data analysis in grounded theory studies. Alternative approaches to qualitative analysis. Integrating qualitative and quantitative data in multi-strategy designs. Chapter 18 Reporting and Disseminating. Introduction. Reporting what you have found. Ethics and reporting. Reporting fixed design research. The scientific journal format. Reporting flexible design studies. Reporting on multi-strategy design studies. Reporting on case studies. Writing for non-academic audiences – the technical report. Alternative forms of presentation. Writing skills. Appendix A: Using Specialist Software for Quantitative Analysis. Appendix B: Using Specialist Software for Qualitative Analysis. Glossary. References and Author Index. Subject Index.

Read more less

Book SynopsisTest scores are the go-to metric of policy makers and anxious parents looking to place their children in the best schools. Yet standardized tests are a poor way to measure school performance. Using the diverse urban school district of Somerville MA as a case study, Jack Schneider’s team developed a new framework to assess educational effectiveness.Trade ReviewIn the K–12 arena, I recommend Jack Schneider’s Beyond Test Scores: A Better Way to Measure School Quality for an approach that gets us past the testing charade and reintroduces some of the values we used to associate with ‘good’ schools. -- John Warner * Inside Higher Ed *Everyone cares about ‘good’ schools but, as Schneider makes painfully clear in this well-written book, almost no one agrees on what constitutes a ‘good’ school. By broadening the story to talk about what we mean when we discuss school quality, he makes a critical contribution to policy, discourse, and the public good. This is a great book about an important subject that gets at the heart of American inequality. -- Tressie McMillan Cottom, author of Lower EdIn this engaging, provocative, and at times inspiring book, Jack Schneider not only asks how we can go beyond standard measures of scholastic achievement—he details an approach that is at once original and practical. -- Howard Gardner, author of The App GenerationA clear-eyed, thoughtful step forward in an endeavor everyone should care about: finding out more about how our schools are doing. -- Anya Kamenetz, author of The TestIn this thoughtful and thorough account, Schneider writes about issues that are critical to the future of education and our efforts to ensure that all students have access to good schooling. For those who are ready to move beyond the polarized debates over standardized testing, this book will be enlightening and a breath of fresh air. -- Pedro Noguera, author of Schooling for ResilienceIn this important book, Schneider asks us to reconsider the purpose of schools and how we evaluate them. He reminds us that public schools are a public good, and that their original purpose was to foster the development of good citizens. -- Diane Ravitch, author of Reign of ErrorBy rooting the discussion in what we value, [Schneider] creates a true framework for making informed choices, challenging the ‘failing schools’ narrative by putting test scores in their proper, limited place. -- John Warner * Chicago Tribune *

Read more less

Book SynopsisGame theory is central to understanding human behavior and relevant to all of the behavioral sciences - from biology and economics, to anthropology and political science. This title demonstrates, game theory alone cannot fully explain human behavior and should instead complement other key concepts championed by the behavioral disciplines.Trade Review"The Bounds of Reason appears as two books in one. One part develops an epistemic theory of the rational actor as an alternative to what is provided by classical game theory, and the other part is a spirited plea to use behavioral game theory as a unifying tool in all behavioral sciences. Both objectives are highly valuable, but combing them both creates friction. Friction creates heat, and Gintis, who thrives gleefully on controversial issues, may be enjoying the prospect of heated discussions."--Karl Sigmund, American Scientist "Gintis' work reflects an amazing breadth of knowledge of the behavioural sciences. He is ever ready to pose unusual questions and to defend unorthodox proposals. The Bounds of Reason is Gintis' most ambitious project to date, one that draws upon all of his extraordinary originality and learning."--Peter Vanderschraaf, Journal of Economics and Philosophy "The book is a combination of an excellent textbook on game theory and an innovation treatise advocating the unification of the behavioural sciences and refounding of game theory on different epistemic foundations... It is clearly an important contribution to the current debate over the rational actor model that the rise of behaviourial economics has provoked."--OxonomicsTable of ContentsPreface xi 1 Decision Theory and Human Behavior 1 1.1 Beliefs, Preferences, and Constraints 4 1.2 The Rationality of Time Inconsistency 9 1.3 Bayesian Rationality and Subjective Priors 12 1.4 Preferences Are State-Dependent 16 1.5 The Behavioral Revolution 18 2 Game Theory: Basic Concepts 33 2.1 The Extensive Form 33 2.2 The Normal Form 36 2.3 Nash Equilibrium 38 2.4 Correlated Equilibrium 47 3 Game Theory and Human Behavior 48 3.1 Behavioral Game Theory 49 3.2 Character Virtues 76 3.3 The Situational Character of Preferences 78 3.4 The Dark Side of Altruistic Cooperation 79 3.5 Norms of Cooperation: Cross-Cultural Variation 81 4 Rationalizability and Common Knowledge of Rationality 86 4.1 Dominated and Iteratedly Dominated Strategies 87 4.2 Epistemic Games 94 4.3 Rationalizable Strategies 98 4.4 Common Knowledge of Rationality 100 5 Extensive Form Rationalizability 106 5.1 Backward Induction and Dominated Strategies 106 5.2 CKR Fails off the Backward Induction Path 113 5.3 How to Play the Repeated Prisoner's Dilemma 114 5.4 Backward Induction and Extensive Form CKR 116 5.5 On the Inadmissibility of CKR 120 6 The Logical Antinomies of Knowledge 123 6.1 The Pitfalls of Na..ive Epistemic Logic 123 6.2 The Common Knowledge of Logicality Paradox 124 6.3 The Surprise Examination 125 6.4 The Modal Logic of Knowledge 126 6.5 A Truth That Cannot Be Known 128 7 The Mixing Problem: Purification and Conjectures 131 7.1 The Incoherence of Mixed Strategies 131 7.2 Purifying Mixed Strategies 133 7.3 A Reputational Model of Honesty and Corruption 135 7.4 Epistemic Games: Mixed Strategies as Conjectures 138 8 Bayesian Rationality and Social Epistemology 142 8.1 The Sexes: From Battle to Ballet 143 8.2 The Choreographer Trumps Backward Induction 144 8.3 Convention as Correlated Equilibrium 146 8.4 The Social Epistemology of Common Priors 149 8.5 The Social Epistemology of Common Knowledge 151 8.6 Social Norms 153 8.7 Game Theory and the Evolution of Norms 153 9 Common Knowledge and Nash Equilibrium 156 9.1 Nash Equilibrium in Two-Player Games 156 9.2 The Modal Logic of Common Knowledge 159 9.3 The Commonality of Knowledge 162 9.4 The Demise of Methodological Individualism 171 10 The Analytics of Human Sociality 174 10.1 Explaining Cooperation: An Overview 174 10.2 The Folk Theorem 178 10.3 Cooperation with Private Signaling 186 10.4 One Cheer for the Folk Theorem 188 10.5 Altruistic Punishing in the Public Goods Game 190 10.6 The Failure of Models of Self-Regarding Cooperation 193 11 The Unification of the Behavioral Sciences 194 11.1 Gene-Culture Coevolution: The Biological Model 196 11.2 Biological and Cultural Dynamics 202 11.3 The Socio-Psychological Theory of Norms 204 11.4 Socialization and the Internalization of Norms 206 11.5 Varieties of Behavioral Modeling 207 11.6 Society as a Complex Adaptive System 215 11.7 The Behavioral Disciplines Can Be Unified 219 12 Summary 221 12.1 Game Theory 221 12.2 Commonality of Beliefs 221 12.3 The Limits of Rationality 222 12.4 Social Norms as Correlated Equilibria 222 12.5 Reason Is Bounded by Sociality, Not Irrationality 223 13 Table of Symbols 224 References 226 Subject Index 254 Author Index 258

Read more less

Book SynopsisA comprehensive and accessible guide to learning and successfully applying QCA Social phenomena can rarely be attributed to single causes—instead, they typically stem from a myriad of interwoven factors that are often difficult to untangle. Drawing on set theory and the language of necessary and sufficient conditions, qualitative comparative analysis (QCA) is ideally suited to capturing this causal complexity. A case-based research method, QCA regards cases as combinations of conditions and compares the conditions of each case in a structured way to identify the necessary and sufficient conditions for an outcome. Qualitative Comparative Analysis: An Introduction to Research Design and Application is a comprehensive guide to QCA. As QCA becomes increasingly popular across the social sciences, this textbook teaches students, scholars, and self-learners the fundamentals of the method, research design, interpretation of results, and how to communicate findings. Following an ideal typical research cycle, the book’s ten chapters cover the methodological basis and analytical routine of QCA, as well as matters of research design, causation and causal complexity, QCA variants, and the method’s reception in the social sciences. A comprehensive glossary helps to clarify the meaning of frequently used terms. The book is complemented by an accessible online R manual to help new users to practice QCA’s analytical steps on sample data and then implement with their own findings. This hands-on textbook is an essential resource for students and researchers looking for a complete and up-to-date introduction to QCA.Trade ReviewMello’s book especially stands out from other publications on QCA in three different areas: the chapters on research design (Chapter II), QCA and its critics (Chapter IX) and the online ‘R Manual’ that accompanies the publication. These elements are especially interesting given the fact they are not discussed in many texts on QCA, thus filling an additional gap in the literature on the method. * Political Studies Review *Table of ContentsList of Boxes, Figures, and Tables Preface Acknowledgments 1. Introduction What Is Qualitative Comparative Analysis? How To Use This Book The QCA Research Cycle A Brief History of QCA Trends in QCA Applications Book Outline Notes 2. Research Design Research Questions Uses of QCA Case Selection Condition Selection Multi-Method Research Designs A Survey of Empirical Applications Notes 3. Set Theory Crisp and Fuzzy Sets Set Operations Truth Tables Necessary and Sufficient Conditions Assessing Set Relations Notes 4. Causation and Causal Complexity Theories of Causation in the Social Sciences Causal Complexity Causal Analysis Notes 5. Calibrating Sets Measurement and Calibration Calibration Procedures Types of Data The Direct Method of Calibration Calibration: Applied Examples Common Misconceptions about Calibration Good Practices of Calibration Notes 6. Measures of Fit Set-Theoretic Consistency Set-Theoretic Coverage Proportional Reduction in Inconsistency Relevance of Necessity Notes 7. Set-Theoretic Analysis Analyzing Necessary Conditions Truth Table Construction Truth Table Analysis Solution Terms Counterfactual Analysis Notes 8. QCA Variants Multi-Value QCA Temporal QCA Two-Step QCA Fuzzy Set Ideal Type Analysis Related Methods and Approaches Notes 9. QCA and Its Critics Analytical Robustness Comparisons with Other Methods Formalization and Algorithms Causal Analysis and Solution Terms Recognizing QCA’s Strengths and Limitations Notes 10. Conclusion Good Research Practice Documenting and Communicating QCA Results QCA Resources The Way Ahead Notes Appendix: Link to Online R Manual Glossary References Index About the Author

Read more less

Book SynopsisCo-authored by an international team of experts across disciplines, this important book is one of the first to demonstrate the enormous benefit creative methods offer for education research. It illustrates how using creative methods, such as poetic inquiry, theatre and animation, can support learning and illuminate participation and engagement.Trade Review"This is a well-written, accessible and thought-provoking book that promotes the use of creative methods in educational research in a balanced way... I am very glad to have the book on my shelf and would definitely recommend it to students, but also to researchers wanting to reflect on their practice." International Journal of Research & Method in Education“While giving clear and practical advice, with lots of case study examples, the book also speaks with a friendly authority that makes it feel both reassuring and inspiring.” Social Research Association Research MattersTable of ContentsIntroduction Research Design Context-Setting Data Gathering Using Two Dimensional and Technological Methods – Research With Children and Young People Data Gathering Using Three Dimensional and Online Methods – Research With Adults Data Analysis Writing/Reporting Presentation Dissemination Where to Next With Creative Research Methods

Read more less