The study of intuition and its relation to thoughtful reasoning is a burgeoning research topic in psychology and beyond. While the area has the potential to radically transform our conception of the mind and decision making, the procedures used for establishing empirical conclusions have often been vaguely formulated and obscure. This book fills a gap in the field by providing a range of methods for exploring intuition experimentally and thereby enhancing the collection of new data. The book begins by summarizing current challenges in the study of intuition and gives a new foundation for intuition research. Going beyond classical dual-process models, a new scheme is introduced to classify the different types of processes usually collected under the label of intuition. These new classifications range from learning approaches to complex cue integration models. The book then goes on to describe the wide variety of behavioural methods available to investigate these processes, including information search tracing, think aloud protocols, maximum likelihood methods, eye-tracking, and physiological and non-physiological measures of affective responses. It also discusses paradigms to investigate implicit associations and causal intuitions, video-based approaches to expert research, methods to induce specific decision modes as well as questionnaires to assess individual preferences for intuition or deliberation. By uniquely providing the basis for exploring intuition by introducing the different methods and their applications in a step-by-step manner, this text is an invaluable reference for individual research projects. It is also very useful as a course book for advanced decision making courses, and could inspire experimental explorations of intuition in psychology, behavioural economics, empirical legal studies and clinical decision making.

An overview is given of cross-cultural psychology and cultural psychology, focusing on theory and methodology. In Section 1 historical developments in research are traced; it is found that initially extensive psychological differences tend to shrink when more carefully designed studies are conducted. Section 2 addresses the conceptualization of "culture" and of "a culture". For psychological research the notion "culture" is considered too vague; more focal explanatory concepts are required. Section 3 describes methodological issues, taking the notion of the empirical cycle as a lead for both qualitative and quantitative research. Pitfalls in research design and data analysis of behavior-comparative studies, and the need for replication are discussed. Section 4 suggests to move beyond research on causal relationships and to incorporate additional questions, addressing the function and the development of behavior patterns in ontogenetic, phylogenetic and historical time. Section 5 emphasizes the need for applied research serving the global village.

Psychologists are under increasing pressure to demonstrate the ecological validity of their assessment procedures--to show that the recommendations concluding their evaluations are relevant to urgent concerns in the legal and social policy arenas, such as predicting dangerousness, awarding compensation, and choosing a custodial parent. How much damage does a referred patient have? Who or what "caused" the damage? What impact will it have on his or her future life, work, and family? And what can be done to remediate the damage? The purpose of this book is to provide sound objective methods for answering these questions. It integrates the knowledge of experienced practitioners who offer state-of-the-art summaries of the best current approaches to evaluating difficult cases with that of basic theorists who describe emerging methods in both predictive and inferential statistics, such as Bayesian networks, that have proven their value in other scientific fields. Arguably, the enterprise of psychological assessment is so interdependent with that of data analysis that attempts to make inferences without consideration of statistical implications is malpractice. Prediction in Forensic and Neuropsychology: Sound Statistical Practices clarifies the process of hypothesis testing and helps to push the clinical interpretation of psychological data into the 21st century. It constitutes a vital resource for all the stakeholders in the assessment process--practitioners, researchers, attorneys, and policymakers.

This book highlights the effects of the COVID-19 pandemic on the mental health needs of children and adolescents in order to shed light on future practice and reform needed to better deal with the aftermath of such devastating events. The book identifies the conditions during any public health crisis that heighten the mental health needs of children and adolescents and suggests the reforms of mental health services needed to better meet the needs of children and youths during and following pandemics and other public health crises. Importance is placed not only on addressing the effects of COVID-19 but on anticipating and preparing for other public health disruptions to the lives of those who have not reached adulthood. Although mental health services in all settings are considered, special attention is given to the role of schools in providing for the mental health of children and adolescents and preparing for the mental health implications of future public health disruptions. The book will be of equal use to both students and researchers in the fields of mental health, well-being, and education as well as teachers, educational psychologists, social workers, and practitioners working in schools and communities to address students' mental health needs. It will help readers better understand how and why COVID-19 was a negative influence on students' mental health, and unpack how best to deal with the aftermath of the pandemic.

The motivation for this volume in the History and Theory of Psychology series is to look across sub-disciplines within psychology and highlight instances where researchers transcended the tendency to think about methodology along traditional lines. Contributors have located examples of researchers who built upon existing ideas to create methods true to their interests and theoretical convictions.

Emerging Methods in Psychology shows how a discipline creates new methods and carves out possibilities that not only generate data, but also advance knowledge of human psychological functioning. It concentrates on showcasing the possibilities that exist when the researcher focuses on the relationship between theory, method, and data.

The question of what kind of expertise is required is a key issue. This is particularly the case in psychology where the tradition of standardizing methods over the last century has served to stabilize research questions. Knowledge creation is deeply affective and ambiguous rather than the secure accumulation of data by a socially legitimized procedure. This innovative volume moves beyond psychology as social engineering into new varieties of social knowledge.

This book shows readers how to conduct observational methods, research tools used to describe and explain behaviors as they unfold in everyday settings. The book now uses both an evolutionary and a cultural perspective. The methods presented are drawn from psychology, education, family studies, sociology, and anthropology, but the author's primary focus is on children in school, family, and social settings. Readers learn how to make observations in real contexts to help them create a verbal picture of behaviors they see. The importance of considering reliability and validity factors while testing within each environment is emphasized throughout. The author draws from the literature that provides methods for observing animals in their natural habitats, but emphasizes the use of observational methods to solve human problems. The book is organized in the way a researcher conducts observational studiesOCoconceptualizing of the idea, designing and implementing the study, and writing the report. OC Things to think aboutOCO sections provide an opportunity for students to solidify their understanding of the material and the Glossary defines the key terms introduced in the book.

Highlights of changes in the new edition include:

OCoaThe introduction of the cultural perspective in chapter 4 along with the evolutionary (epigenetic theory) perspective and the integration of cultural examples throughout the book.
OCoaMore varied examples from developmental psychology, family studies, and education.
OCoaExtensively revised chapter (3) on ethics reflects the current revelations of scientific fraud and the push for researchers to maximize scientific integrity in their community.
OCoaUpdated chapter (12) reflects the latest computer technologies used in observational methods including iPhones and Blackberrys for conducting observation, ABC Data Pro and Behavior Tracker for evaluations, and Excel for constructing observational templates.
OCoaExpanded chapter (13) on writing the research report and more on issues of plagiarism (ch. 3).a
OCoaThe latest on minimizing observer effects on participants and testing their effectiveness.
OCoaNew environmentally friendly design, the Things to Think About sections were retained, but the blank pages for answers were eliminated.

Intended as a supplementary text for advanced undergraduate and/or graduate courses in research methods and/or developmental research or developmental/child psychology taught in psychology, education, human development, and nursing, educators and researchers concerned with assessing children will also appreciate this bookOCOs introduction to observational methods.

This is the first workbook that introduces the multilevel approach to modeling with categorical outcomes using IBM SPSS Version 20. Readers learn how to develop, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers through data management, diagnostic tools, model conceptualization, and model specification issues related to single-level and multilevel models with categorical outcomes. Screen shots clearly demonstrate techniques and navigation of the program. Modeling syntax is provided in the appendix. Examples of various types of categorical outcomes demonstrate how to set up each model and interpret the output. Extended examples illustrate the logic of model development, interpretation of output, the context of the research questions, and the steps around which the analyses are structured. Readers can replicate examples in each chapter by using the corresponding data and syntax files available at www.psypress.com/9781848729568. The book opens with a review of multilevel with categorical outcomes, followed by a chapter on IBM SPSS data management techniques to facilitate working with multilevel and longitudinal data sets. Chapters 3 and 4 detail the basics of the single-level and multilevel generalized linear model for various types of categorical outcomes. These chapters review underlying concepts to assist with trouble-shooting common programming and modeling problems. Next population-average and unit-specific longitudinal models for investigating individual or organizational developmental processes are developed. Chapter 6 focuses on single- and multilevel models using multinomial and ordinal data followed by a chapter on models for count data. The book concludes with additional trouble shooting techniques and tips for expanding on the modeling techniques introduced. Ideal as a supplement for graduate level courses and/or professional workshops on multilevel, longitudinal, latent variable modeling, multivariate statistics, and/or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this practical workbook also appeals to researchers in these fields. An excellent follow up to the authors' highly successful Multilevel and Longitudinal Modeling with IBM SPSS and Introduction to Multilevel Modeling Techniques, 2nd Edition, this book can also be used with any multilevel and/or longitudinal book or as a stand-alone text introducing multilevel modeling with categorical outcomes.

Now in its fourth edition, Behavioral Research and Analysis: An Introduction to Statistics within the Context of Experimental Design presents an overview of statistical methods within the context of experimental design. It covers fundamental topics such as data collection, data analysis, interpretation of results, and communication of findings. New in the Fourth Edition: Extensive improvements based on suggestions from those using this book in the classroom Statistical procedures that have been developed and validated since the previous edition Each chapter in the body now contains relevant key words, chapter summaries, key word definitions, and end of chapter exercises (with answers) Revisions to include recent changes in the APA Style Manual When looking for a book for their own use, the authors found none that were totally suitable. They found books that either reviewed the basics of behavioral research and experimental design but provided only cursory coverage of statistical methods or they provided coverage of statistical methods with very little coverage of the research context within which these methods are used. No single resource provided coverage of methodology, statistics, and communication skills. In a classic example of necessity being the mother of invention, the authors created their own. This text is ideal for a single course that reviews research methods, essential statistics through multi-factor analysis of variance, and thesis (or major project) preparation without discussion of derivation of equations, probability theory, or mathematic proofs. It focuses on essential information for getting a research project completed without prerequisite math or statistics training. It has been revised many times to help students at a variety of academic levels (exceptional high school students, undergraduate honors students, masters students, doctoral students, and post-doctoral fellows) across varied academic disciplines (e.g., human factors and ergonomics, behavioral and social sciences, natural sciences, engineering, exercise and sport sciences, business and management, industrial hygiene and safety science, health and medical sciences, and more). Illustrating how to plan, prepare, conduct, and analyze an experimental or research report, the book emphasizes explaining statistical procedures and interpreting obtained results without discussing the derivation of equations or history of the method. Destined to spend more time on your desk than on the shelf, the book will become the single resource you reach for again and again when conducting scientific research and reporting it to the scientific community. Illustrates how to plan, conduct, analyze, and prepare an experimental or research report Includes new statistical procedures that have been developed and validated since the previous edition Incorporates SAS in the exercises at the end of each chapter Takes into account the changes in the APA guidebook Provides new examples in exercise and sport science, public health, gerontology, and biomedical areas Solutions manual available upon qualifying course adoption

An up-to-date book about art through the lens of neuroscience and psychology. In Creativity & Art, Andreas and Barbara Steck use an interdisciplinary approach to discuss creative processes from a neuroscientific and psychoanalytic perspective. By referring to the current knowledge of brain sciences, the authors explore the understanding of the neural bases innate to the creation of art. Beginning with historical aspects of aesthetic experience and creation in ancient and modern times, the authors go on to present numerous artists in various fields, with an emphasis on how their subjective lived experiences are expressed and reflected in their artwork. Finally, the Stecks describe the building blocks of creativity in early childhood development discuss the psychoanalytic understanding of human aesthetic experience and creativity. Insightful and thought-provoking, Creativity & Art examines art through the lens of neuroscience and psychology.

Although its roots can be traced to the 19th century, progress in the study of nonlinear dynamical systems has taken off in the last 30 years. While pertinent source material exists, it is strewn about the literature in mathematics, physics, biology, economics, and psychology at varying levels of accessibility. A compendium research methods reflecting the expertise of major contributors to NDS psychology, Nonlinear Dynamical Systems Analysis for the Behavioral Sciences Using Real Data examines the techniques proven to be the most useful in the behavioral sciences. The editors have brought together constructive work on new practical examples of methods and application built on nonlinear dynamics. They cover dynamics such as attractors, bifurcations, chaos, fractals, catastrophes, self-organization, and related issues in time series analysis, stationarity, modeling and hypothesis testing, probability, and experimental design. The analytic techniques discussed include several variants of the fractal dimension, several types of entropy, phase-space and state-space diagrams, recurrence analysis, spatial fractal analysis, oscillation functions, polynomial and Marquardt nonlinear regression, Markov chains, and symbolic dynamics. The book outlines the analytic requirements faced by social scientists and how they differ from those of mathematicians and natural scientists. It includes chapters centered on theory and procedural explanations for running the analyses with pertinent examples and others that illustrate applications where a particular form of analysis is seen in the context of a research problem. This combination of approaches conveys theoretical and practical knowledge that helps you develop skill and expertise in framing hypotheses dynamically and building viable analytic models to test them.

This latest edition has been fully updated to accommodate the needs of users of SPSS Releases 17, 18 and 19 while still being applicable to users of SPSS Releases 15 and 16. As with previous editions, Alan Bryman and Duncan Cramer continue to offer a comprehensive and user-friendly introduction to the widely used IBM SPSS Statistics. The simple, non-technical approach to quantitative data analysis enables the reader to quickly become familiar with SPSS and with the tests available to them. No previous experience of statistics or computing is required as this book provides a step-by-step guide to statistical techniques, including: Non-parametric tests Correlation Simple and multiple regression Analysis of variance and covariance Factor analysis. This book comes equipped with a comprehensive range of exercises for further practice, and it covers key issues such as sampling, statistical inference, conceptualization and measurement and selection of appropriate tests. The authors have also included a helpful glossary of key terms. The data sets used in Quantitative Data Analysis with IBM SPSS 17, 18 and 19 are available online at http://www.routledgetextbooks.com/textbooks/_author/bryman-9780415579193/; in addition, a set of multiple-choice questions and a chapter-by-chapter PowerPoint lecture course are available free of charge to lecturers who adopt the book.

This book reviews the statistical procedures used to detect measurement bias. Measurement bias is examined from a general latent variable perspective so as to accommodate different forms of testing in a variety of contexts including cognitive or clinical variables, attitudes, personality dimensions, or emotional states. Measurement models that underlie psychometric practice are described, including their strengths and limitations. Practical strategies and examples for dealing with bias detection are provided throughout. The book begins with an introduction to the general topic, followed by a review of the measurement models used in psychometric theory. Emphasis is placed on latent variable models, with introductions to classical test theory, factor analysis, and item response theory, and the controversies associated with each, being provided. Measurement invariance and bias in the context of multiple populations is defined in chapter 3 followed by chapter 4 that describes the common factor model for continuous measures in multiple populations and its use in the investigation of factorial invariance. Identification problems in confirmatory factor analysis are examined along with estimation and fit evaluation and an example using WAIS-R data. The factor analysis model for discrete measures in multiple populations with an emphasis on the specification, identification, estimation, and fit evaluation issues is addressed in the next chapter. An MMPI item data example is provided. Chapter 6 reviews both dichotomous and polytomous item response scales emphasizing estimation methods and model fit evaluation. The use of models in item response theory in evaluating invariance across multiple populations is then described, including an example that uses data from a large-scale achievement test. Chapter 8 examines item bias evaluation methods that use observed scores to match individuals and provides an example that applies item response theory to data introduced earlier in the book. The book concludes with the implications of measurement bias for the use of tests in prediction in educational or employment settings. A valuable supplement for advanced courses on psychometrics, testing, measurement, assessment, latent variable modeling, and/or quantitative methods taught in departments of psychology and education, researchers faced with considering bias in measurement will also value this book.

The Student Study Guide With SPSS Workbook for Essential Statistics for the Behavioral Sciences includes a review of chapter learning objectives, chapter outlines and key terms, essential statistical formulas, special tips and insights for students, and chapter summaries. To help students practice skills, the guide offers word searches and crossword puzzles for each chapter, extensive practice quizzes linked to chapter learning objectives, and "SPSS in Focus" exercises which complement those in the book.

Neil J. Salkind's best-selling Statistics for People Who (Think They) Hate Statistics has been helping ease student anxiety around an often intimidating subject since it first published in 2000. Now the bestselling SPSS and Excel versions are joined by a first edition of the text for use with the R software. New co-author Leslie A. Shaw carries forward Neil's signature humorous, personable, and informative approach. The text guides students through various statistical procedures, beginning with descriptive statistics, correlation, and graphical representation of data, and ending with inferential techniques and analysis of variance. Features and benefits: * Lots of support for getting started with R: Included are two introductory chapters on R and on R Studio, plus an appendix on other R packages and resource sites. * Step-by-step demonstrations of each statistical procedure in R: The authors show how to import the dataset, enter the syntax to run the test, and understand the output. * Additional resources make it easy to transition to this text, and to R: Code and datasets are available on an accompanying website, which also includes screencast R tutorial videos for students, and PowerPoint slides and additional test questions for instructors.

Highlighting the progress made by researchers in using Web-based surveys for data collection, this timely volume summarizes the experiences of leading behavioral and social scientists from Europe and the US who collected data using the Internet. Some chapters present theory, methodology, design, and implementation, while others focus on best practice examples and/or issues such as data quality and understanding paradata. A number of contributors applied innovative Web-based research methods to the LISS panel of CentERdata collected from over 5,000 Dutch households. Their findings are presented in the book. Some of the data is available on the book website. The book addresses practical issues such as data quality, how to reach difficult target groups, how to design a survey to maximize response, and ethical issues that need to be considered. Innovative applications such as the use of biomarkers and eye-tracking techniques are also explored. Part 1 provides an overview of Internet survey research including its methodologies, strengths, challenges, and best practices. Innovative ways to minimize sources of error are provided along with a review of mixed-mode designs, how to design a scientifically sound longitudinal panel and avoid sampling problems, and address ethical requirements in Web surveys. Part 2 focuses on advanced applications including the impact of visual design on the interpretability of survey questions, the impact survey usability has on respondents' answers, design features that increase interaction, and how Internet surveys can be effectively used to study sensitive issues. Part 3 addresses data quality, sample selection, measurement and non-response error, and new applications for collecting online data. The issue of underrepresentation of certain groups in Internet research and the measures most effective at reducing it are also addressed. The book concludes with a discussion of the importance of paradata and the Web data collection process in general, followed by chapters with innovative experiments using eye-tracking techniques and biomarker data. This practical book appeals to practitioners from market survey research institutes and researchers in disciplines such as psychology, education, sociology, political science, health studies, marketing, economics, and business who use the Internet for data collection, but is also an ideal supplement for graduate and/or upper level undergraduate courses on (Internet) research methods and/or data collection taught in these fields.

This book is open access under a CC BY-NC 2.5 license. This book describes the extensive contributions made toward the advancement of human assessment by scientists from one of the world's leading research institutions, Educational Testing Service. The book's four major sections detail research and development in measurement and statistics, education policy analysis and evaluation, scientific psychology, and validity. Many of the developments presented have become de-facto standards in educational and psychological measurement, including in item response theory (IRT), linking and equating, differential item functioning (DIF), and educational surveys like the National Assessment of Educational Progress (NAEP), the Programme of international Student Assessment (PISA), the Progress of International Reading Literacy Study (PIRLS) and the Trends in Mathematics and Science Study (TIMSS). In addition to its comprehensive coverage of contributions to the theory and methodology of educational and psychological measurement and statistics, the book gives significant attention to ETS work in cognitive, personality, developmental, and social psychology, and to education policy analysis and program evaluation. The chapter authors are long-standing experts who provide broad coverage and thoughtful insights that build upon decades of experience in research and best practices for measurement, evaluation, scientific psychology, and education policy analysis. Opening with a chapter on the genesis of ETS and closing with a synthesis of the enormously diverse set of contributions made over its 70-year history, the book is a useful resource for all interested in the improvement of human assessment.

The encouraging book that has guided thousands of students step by step through crafting a strong dissertation proposal is now in a thoroughly revised second edition. It includes new guidance for developing methodology-specific problem statements, an expanded discussion of the literature review, coverage of the four-chapter dissertation model, and more. Terrell demonstrates how to write each chapter of the proposal, including the problem statement, purpose statement, and research questions and hypotheses; literature review; and detailed plans for data collection and analysis. "Let's Start Writing" exercises serve as building blocks for drafting a complete proposal. Other user-friendly features include case-study examples from diverse disciplines, "Do You Understand?" checklists, and end-of-chapter practice tests with answers. Appendices present an exemplary proposal written three ways to demonstrate quantitative, qualitative, and mixed methods approaches, and discuss how to structure a four-chapter dissertation. New to This Edition *Introduction offering a concise overview of the entire proposal-writing process and the doctoral experience. *Additional help with tailoring problem and purpose statements for quantitative, qualitative, and mixed-methods studies. *Expanded discussion of the review of literature, including a criterion for judging the quality of primary versus secondary sources. *Many new examples from different disciplines, such as studies of depression treatments, approaches to reducing offender recidivism, health effects of irradiated crops, strength training in college football, and remote teaching and learning during COVID-19. *Focus on the five-chapter model is broadened to include specific guidance for four-chapter dissertations. *Broader, more detailed reference list and glossary.

This book offers a critical perspective of the dominant discourses within the field of psychological trauma. It provides a challenge to normative western constructs and unsettles assumptions about accepted notions of universality and the nature of trauma. Traditionally the concept of psychological trauma has been widely accepted within mental health professions. However, in a post-positivist era, the language of mental health is shifting and making room for alternative discourses that include wider contextual influences, such as the impact of sociological, cultural, and technological developments. These wider discourses are illuminated as the authors draw together some of these arguments into one accessible text. Rather than claim definitive answers to the issues raised, readers are invited to engage with the discussions presented in order to position themselves in relation to the range of trauma discourses available.

This proceedings volume highlights the latest research and developments in psychometrics and statistics. It represents selected and peer-reviewed presentations given at the 85th Annual International Meeting of the Psychometric Society (IMPS), held virtually on July 13-17, 2020. The IMPS is one of the largest international meetings on quantitative measurement in education, psychology and the social sciences. It draws approximately 500 participants from around the world, featuring paper and poster presentations, symposiums, workshops, keynotes, and invited presentations. Leading experts and promising young researchers have written the included chapters. The chapters address a wide variety of topics including but not limited to item response theory, adaptive testing, Bayesian estimation, propensity scores, and cognitive diagnostic models. This volume is the 9th in a series of recent works to cover research presented at the IMPS.

Significantly revised, the fifth edition of the most complete, accessible text now covers all three approaches to structural equation modeling (SEM)--covariance-based SEM, nonparametric SEM (Pearl's structural causal model), and composite SEM (partial least squares path modeling). With increased emphasis on freely available software tools such as the R lavaan package, the text uses data examples from multiple disciplines to provide a comprehensive understanding of all phases of SEM--what to know, best practices, and pitfalls to avoid. It includes exercises with answers, rules to remember, topic boxes, and a new self-test on significance testing, regression, and psychometrics. The companion website supplies helpful primers on these topics as well as data, syntax, and output for the book's examples, in files that can be opened with any basic text editor. New to This Edition *Chapters on composite SEM, also called partial least squares path modeling or variance-based SEM; conducting SEM analyses in small samples; and recent developments in mediation analysis. *Coverage of new reporting standards for SEM analyses; piecewise SEM, also called confirmatory path analysis; comparing alternative models fitted to the same data; and issues in multiple-group SEM. *Extended tutorials on techniques for dealing with missing data in SEM and instrumental variable methods to deal with confounding of target causal effects. Pedagogical Features *New self-test of knowledge about background topics (significance testing, regression, and psychometrics) with scoring key and online primers. *End-of-chapter suggestions for further reading and exercises with answers. *Troublesome examples from real data, with guidance for handling typical problems in analyses. *Topic boxes on special issues and boxed rules to remember. *Website promoting a learn-by-doing approach, including data, extensively annotated syntax, and output files for all the book's detailed examples.

Assessing Competencies for Social and Emotional Learning explores the conceptualization, development, and application of assessments of competencies and contextual factors related to social and emotional learning (SEL). As programs designed to teach students social and emotional competencies are being adopted at an ever-increasing rate, new measurements are needed to understand their impact on student attitudes, behaviors, and academic performance. This book integrates standards of fairness, reliability, and validity, and lessons learned from personality and attitude assessment to facilitate the principled development and use of SEL assessments. Education professionals, assessment developers, and researchers will be better prepared to systematically develop and evaluate measures of social and emotional competencies.

This book proposes and explores the idea that the forced union of the aleatory and epistemic aspects of probability is a sterile hybrid, inspired and nourished for 300 years by a false hope of formalizing inductive reasoning, making uncertainty the object of precise calculation. Because this is not really a possible goal, statistical inference is not, cannot be, doing for us today what we imagine it is doing for us. It is for these reasons that statistical inference can be characterized as a myth. The book is aimed primarily at social scientists, for whom statistics and statistical inference are a common concern and frustration. Because the historical development given here is not merely anecdotal, but makes clear the guiding ideas and ambitions that motivated the formulation of particular methods, this book offers an understanding of statistical inference which has not hitherto been available. It will also serve as a supplement to the standard statistics texts. Finally, general readers will find here an interesting study with implications far beyond statistics. The development of statistical inference, to its present position of prominence in the social sciences, epitomizes a number of trends in Western intellectual history of the last three centuries, and the 11th chapter, considering the function of statistical inference in light of our needs for structure, rules, authority, and consensus in general, develops some provocative parallels, especially between epistemology and politics.

This book explores how discursive psychology (DP) research can be applied to disability and the everyday and institutional constructions of bodymind differences. Bringing together both theoretical and empirical work, it illustrates how DP might be leveraged to make visible nuanced understandings of disability and difference writ large. The authors argue that DP can attend to how such realities are made relevant, dealt with, and negotiated within social practices in the study of disability. They contend that DP can be used to unearth the nuanced and frequently taken for granted ways in which disability is made real in both everyday and institutional talk, and can highlight the very ways in which differences are embodied in social practices - specifically at the level of talk and text. This book demonstrates that rather than simply staying at the level of theory, DP scholars can make visible the actual means by which disabilities and differences more broadly are made real, resisted, contested, and negotiated in everyday social actions. This book aims to expand conceptions of disability and to deepen the - at present, primarily theoretical - critiques of medicalization.

Good Science is an account of psychological research emphasizing the moral foundations of inquiry. This volume brings together existing disciplinary critiques of scientism, objectivism, and instrumentalism, and then discusses how these contribute to institutionalized privilege and to less morally responsive research practices. The author draws on historical, critical, feminist, and science studies traditions to provide an alternative account of psychological science and to highlight the irreducibly moral foundations of everyday scientific practice. This work outlines a theoretical framework for thinking about and practicing psychology in ways that center moral responsibility, collective commitment, and justice. The book then applies this framework, describing psychological research practices in terms of the their moral dilemmas. Also included are materials meant to aid in methods instruction and mentoring.