This book is a first attempt to combine insights from the two perspectives with regard to the question of meaning by examining a collection of theoretical and empirical works. This volume therefore is destined to become an important addition to psychological literature: both from the viewpoint of the history of ideas (again this would be one of the first times that positive and existentialist psychologies meet) and from the viewpoint of theoretical and empirical research into the meaning concept in psychology.

This is an international and interdisciplinary volume that provides a new look at the general background of the social sciences from a philosophical perspective and provides directions for methodology. It seeks to overcome the limitations of the traditional treatises of a philosophy of science rooted in the physical sciences, as well as extend the coverage of basic science to intentional and socially normative features of the social sciences. The discussions included in this book are divided into four thematic sections: Social and cognitive roots for reflexivity upon the research process Philosophies of explanation in the social sciences Social normativity in social sciences Social processes in particular sciences Social Philosophy of Science for the Social Sciences will find an interested audience in students of the philosophy of science and social sciences. It is also relevant for researchers and students in the fields of psychology, sociology, economics, anthropology, education, and political science.

This book proposes a novel view to explain how we as humans -- contrary to current robots -- can have the impression of consciously feeling things: for example the red of a sunset, the smell of a rose, the sound of a symphony, or a pain.
The book starts off by looking at visual perception. Our ability to see turns out to be much more mysterious than one might think. The eye contains many defects which should seriously interfere with vision. Yet we have the impression of seeing the world in glorious panavision and technicolor. Explaining how this can be the case leads to a new idea about what seeing really is. Seeing is not passively receiving information in the brain, but rather a way of interacting with the world. The role of the brain is not to create visual sensation, but to enable the necessary interactions with the world.
This new approach to seeing is extended in the second part of the book to encompass the other senses: hearing, touch, taste and smell. Taking sensory experiences to be modes of interacting with the world explains why these experiences are different in the way they are. It also explains why thoughts or automatic functions in the body, and indeed the vast majority brain functions, are not accompanied by any real feeling.
The "sensorimotor" approach is not simply a philosophical argument: It leads to scientifically verifiable predictions and new research directions. Among these are the phenomena of change blindness, sensory substitution, "looked but failed to see," as well as results on color naming and color perception and the localisation of touch on the body.
The approach is relevant to the question of what animals and babies can feel, and to understanding what will be necessary for robots to become conscious.

This textbook considers statistical learning applications when interest centers on the conditional distribution of a response variable, given a set of predictors, and in the absence of a credible model that can be specified before the data analysis begins. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis depends in an integrated fashion on sound data collection, intelligent data management, appropriate statistical procedures, and an accessible interpretation of results. The unifying theme is that supervised learning properly can be seen as a form of regression analysis. Key concepts and procedures are illustrated with a large number of real applications and their associated code in R, with an eye toward practical implications. The growing integration of computer science and statistics is well represented including the occasional, but salient, tensions that result. Throughout, there are links to the big picture. The third edition considers significant advances in recent years, among which are: the development of overarching, conceptual frameworks for statistical learning; the impact of "big data" on statistical learning; the nature and consequences of post-model selection statistical inference; deep learning in various forms; the special challenges to statistical inference posed by statistical learning; the fundamental connections between data collection and data analysis; interdisciplinary ethical and political issues surrounding the application of algorithmic methods in a wide variety of fields, each linked to concerns about transparency, fairness, and accuracy. This edition features new sections on accuracy, transparency, and fairness, as well as a new chapter on deep learning. Precursors to deep learning get an expanded treatment. The connections between fitting and forecasting are considered in greater depth. Discussion of the estimation targets for algorithmic methods is revised and expanded throughout to reflect the latest research. Resampling procedures are emphasized. The material is written for upper undergraduate and graduate students in the social, psychological and life sciences and for researchers who want to apply statistical learning procedures to scientific and policy problems.

Advancing work to effectively study, understand, and serve the fastest growing U.S. ethnic minority population, this volume explicitly emphasizes the racial and ethnic diversity within this heterogeneous cultural group. The focus is on the complex historical roots of contemporary Latino/as, their diversity in skin-color and physiognomy, racial identity, ethnic identity, gender differences, immigration patterns, and acculturation. The work highlights how the complexities inherent in the diverse Latino/a experience, as specified throughout the topics covered in this volume, become critical elements of culturally responsive and racially conscious mental health treatment approaches. By addressing the complexities, within-group differences, and racially heterogeneity characteristic of U.S. Latino/as, this volume makes a significant contribution to the literature related to mental health treatments and interventions.

Single-Case Methods in Clinical Psychology: A Practical Guide provides a concise and easily-accessible introduction to single-case research. This is a timely response to the increasing awareness of the need to look beyond randomised controlled trials for evidence to support best practice in applied psychology. The book covers the issues of design, the reliability and validity of measurement, and provides guidance on how to analyse single-case data using both visual and statistical methods. Single-case designs can be used to investigate an individual's response to psychological intervention, as well as to contribute to larger scale research projects. This book illuminates the common principles behind these uses. It describes how standardised measures can be used to evaluate change in an individual and how to develop idiographic measures that are tailored to the needs of an individual. The issue of replication and generalising beyond an individual are examined, and the book also includes a section on the meta-analysis of single-case data. The critical evaluation of single-case research is examined, from both the perspective of developing quality standards to evaluate research and maintaining a critical distance in reviewing one's own work. Single Case Methods in Clinical Psychology will provide invaluable guidance to postgraduate psychologists training to enter the professions of clinical, health and counselling psychology and is likely to become a core text on many courses. It will also appeal to clinicians seeking to answer questions about the effectiveness of therapy in individual cases and who wish to use the method to further the evidence-base for specific psychological interventions.

Why learn functional programming? Isn't that some complicated ivory-tower technique used only in obscure languages like Haskell? In fact, functional programming is actually very simple. It's also very powerful, as Haskell demonstrates by throwing away all the conventional programming tools and using only functional programming features. But it doesn't have to be done that way. Functional programming is a power tool that you can use in addition to all your usual tools, to whatever extent your current mainstream language supports it. Most languages have at least basic support. In this book we use Python and Java and, as a bonus, Scala. If you prefer another language, there will be minor differences in syntax, but the concepts are the same. Give functional programming a try. You may be surprised how much a single power tool can help you in your day-to-day programming.

With a highly pragmatic, yet rigorous and pragmatically driven approach, this edited book explores demonstrates qualitative research with an applied approach. Using not only theory but real world setting, readers are introduced to the function and relevance of qualitative methods in psychological research. Exemplified through the contributions of various experts from across the different sub-disciplines of psychology, this text takes a versatile approach to explaining methods in research and covers a broad range of methods in a variety of settings. This book will appeal to those with an interest in qualitative methods across the spectrum of psychology and beyond. Offering an introduction to applied qualitative research in psychology with a distinctively applied approach, this title is apt for undergraduate psychology students taking modules in research methods, executing research-based projects or those undertaking Masters and taught doctoral level programs in psychology.

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.

This step-by-step guide shows you how to use R to get data analysis right. The book explores the entire process of analysis, covering key steps from preparing your data to putting your analysis together and writing up your findings. It helps you get to grips with doing different statistical techniques in R and: Equips you with practical data visualisation tools to create graphs and tables. Shows you how to prepare and present your research for assessment, publication and dissemination. Covers key issues facing today's social scientists, such as making research reproducible. Features include an introduction to each chapter, and end-of-chapter exercises to check your understanding of the material. The online resources for this text include data sets that you can perform your own analysis on, and links to publications that are relevant to programming with R. A good starting point for any postgraduate student conducting a research project, this book will help you develop your statistics and programming knowledge and get quickly up to speed.

Missing data affect nearly every discipline by complicating the statistical analysis of collected data. But since the 1990s, there have been important developments in the statistical methodology for handling missing data. Written by renowned statisticians in this area, Handbook of Missing Data Methodology presents many methodological advances and the latest applications of missing data methods in empirical research. Divided into six parts, the handbook begins by establishing notation and terminology. It reviews the general taxonomy of missing data mechanisms and their implications for analysis and offers a historical perspective on early methods for handling missing data. The following three parts cover various inference paradigms when data are missing, including likelihood and Bayesian methods; semi-parametric methods, with particular emphasis on inverse probability weighting; and multiple imputation methods. The next part of the book focuses on a range of approaches that assess the sensitivity of inferences to alternative, routinely non-verifiable assumptions about the missing data process. The final part discusses special topics, such as missing data in clinical trials and sample surveys as well as approaches to model diagnostics in the missing data setting. In each part, an introduction provides useful background material and an overview to set the stage for subsequent chapters. Covering both established and emerging methodologies for missing data, this book sets the scene for future research. It provides the framework for readers to delve into research and practical applications of missing data methods.

Developed and adapted by the authors of this book, thematic analysis (TA) is one of the most popular qualitative data analytic techniques in psychology and the social and health sciences. Building on the success of Braun & Clarke's 2006 paper first outlining their approach - which has over 100,000 citations on Google Scholar - this book is the definitive guide to TA, covering: - Contextualisation of TA - Developing themes - Writing TA reports - Reflexive TA It addresses the common questions surrounding TA as well as developments in the field, offering a highly accessible and practical discussion of doing TA situated within a clear understanding of the wider terrain of qualitative research. Virginia Braun is a Professor in the School of Psychology at The University of Auckland, Aotearoa New Zealand. Victoria Clarke is an Associate Professor in Qualitative and Critical Psychology in the Department of Social Sciences at the University of the West of England (UWE), Bristol.

This book is a seminal guide to loneliness and social isolation in old age, providing a comprehensive overview of the important correlates of socioeconomic, health and lifestyle factors upon loneliness and social isolation in old age. Bringing together contributions from leading authorities, the book showcases expertise from medicine, psychology, epidemiology, sociology, economics and gerontology. It shows the importance of identifying factors associated with loneliness and social isolation among older adults from a broader perspective, and includes discussion of a range of topics including income poverty, physical activity, family care and frailty. The chapters are evidence-based and offer a mix of empirical studies as well as reviews of international research. The book also discusses policy implications and provides an overview of nationally representative cohort studies around the world available to researchers quantifying loneliness or social isolation. This book is unique in examining loneliness and social isolation from such wide-ranging perspectives and will be essential reading for researchers and postgraduate students in the areas of mental health research, social work, and psychiatry. Health professionals involved with gerontology and geriatrics will also find this book of benefit.

Shared and Collaborative Practice in Qualitative Inquiry: Tiny Revolutions is a short collection of reflections on ethical research practice and scholarly community. It explores the qualitative tradition through the process of writing, photography, dance, and narrative. This is a book about ethical research practices, about simple truths, about the commitments we initially made to this work, and about how we might better support each other along the way. Most importantly, this is a book about finding and making our own communities. Communities do not belong to any one person or small group of people. Rather, communities-genuine, real, and vibrant communities-belong to us all. This is a book about how. This book is suitable for people new to qualitative research and seasoned researchers who would like to explore and develop traditions in qualitative inquiry.

Reciprocity Rules explores the rich and complicated relationships that develop between anthropologists and research participants over time. Focusing on compensation and the creation of friendship and "family" relationships, contributors discuss what, when, and how researchers and the people with whom they work give to each other in and beyond fieldwork. Through reflexivity and narrative, the contributors to this edited collection, who are in various stages in their professional careers and whose research spans three continents and eight countries, reflect on the ways in which they have compensated their research participants and given back to host communities, as well as the varied responses to their efforts. The contributors consider both material and non-material forms of reciprocity, stories of successes and failures, and the taken-for-granted notions of compensation, friendship, and "helping." In so doing, they address the interpersonal dynamics of power and agency in the field, examine cultural misunderstandings, and highlight the challenges that anthropologists face as they strive to maintain good relations with their hosts even when separated by time and space. The contributors argue that while learning, following, openly discussing, and writing about the local rules of reciprocity are always challenging, they are essential to responsible research practice and ongoing efforts to decolonize anthropology.

This book provides an in-depth examination of psychosocial marital well-being and mental health in traditional communities in Rwanda. It presents rich qualitative research conducted with men, women and elders, highlighting both the issues impacting on marital conflict and domestic violence, and also how potential solutions might be drawn from traditional practices. In doing, so it provides a unique resource for researchers and policymakers seeking to develop evidence-based and culturally-informed mental health and psychosocial support interventions in low and middle income countries. It will appeal in particular to those working the fields of public health, family psychology, social work, cross-cultural psychology and qualitative methodology.

This book explores the practice and transmission of Lacanian and Freudian theory. It discusses the pure versus applied analysis of Lacanian and Freudian theory in practice; and the hierarchical versus circular transmissions within psychoanalytic organizations. Underpinned by extensive practical knowledge of the clinic, this work examines the differences between Freud and Lacan in their understanding of the subject and the unconscious and pushes them in new directions. The book also offers an analysis and commentary of several key Lacanian texts including an accessible study of the notoriously challenging text L'etourdit. Offering both divergent and reinforcing takes on Lacan, the author explores the traits that separate out the psychoanalyst from other twentieth-century thinkers and theorists. This book offers a clear clinical picture of where Lacanian psychoanalysis is today, both in the US and internationally.

Research Design for the Behavioral Sciences fills an important gap for the helping professions by offering a blueprint for advanced concepts and an applied approach to understanding quantitative, qualitative, and mixed methods research design. This graduate-level text seamlessly weaves together the philosophy, science, and practical application of the most common methodological frameworks in practice. Advanced research design concepts are presented through clear and in-depth blueprints, applied case studies, myriad examples, and helpful learning activities.Written in detailed yet accessible language, this text describes the foundations of behavioral science research. The authors explore research-based philosophical integration, along with the technical application of every tradition. Through this philosophical and pragmatic approach, students will be able to attain a well-rounded and comprehensive understanding of behavioral science research. This text provides students with the opportunity to reach a greater level of research efficacy though the inclusion of methodological procedures, data analysis methods, reliability/validity standards, ethics, and directions on how to increase the rigor of each approach to research. Instructor resources include an instructor's manual, learning activities, test bank, and PowerPoints. Purchase includes digital access for use on most mobile devices and computers. Key Features: Provides clear, detailed, and contextually accurate examples of writing, quantitative, qualitative, and mixed methods procedures Reviews the paradigmatic hierarchy of each research tradition along with key analytic features in detail Delivers instructions for enhancing the methodological rigor of each approach Analyzes methodology-specific multicultural issues Demonstrates the application of a wide range of research methodologies with case studies Reviews the trends and history in research for counseling, psychology, social work, and marriage and family therapy Offers comprehensive instructor resources including manual, learning activities, test bank, and PowerPoint slides

Today, information is very important for businesses. Businesses that use information correctly are successful while those that don't, decline. Social media is an important source of data. This data brings us to social media analytics. Surveys are no longer the only way to hear the voice of consumers. With the data obtained from social media platforms, businesses can devise marketing strategies. It provides a better understanding consumer behavior. As consumers are at the center of all business activities, it is unrealistic to succeed without understanding consumption patterns. Social media analytics is useful, especially for marketers. Marketers can evaluate the data to make strategic marketing plans. Social media analytics and consumer behavior are two important issues that need to be addressed together. The book differs in that it handles social media analytics from a different perspective. It is planned that social media analytics will be discussed in detail in terms of consumer behavior in the book. The book will be useful to the students, businesses, and marketers in many aspects.

Do you want to learn to read people's minds? In this student-friendly, practice-focussed textbook on EEG and biosignal analysis, you will learn how to: Implement your experiment in E-Prime or OpenSesame; Run your study in the psychophysiological laboratory; Analyse data in MATLAB by following simple steps. This textbook follows a unique approach by guiding you through a single EEG study, each part introducing the relevant core knowledge and commonly available software. Practical exercises help you master the skills to independently implement every aspect of an experiment, from setting up the lab to analysing the data. Suitable for developing both basic levels of skill for undergraduates as well as advancing towards a stronger command of analysis and understanding at postgraduate level. Michiel Spape is a Lecturer and Researcher in Psychology at the University of Helsinki.

Do you want to learn to read people's minds? In this student-friendly, practice-focussed textbook on EEG and biosignal analysis, you will learn how to: Implement your experiment in E-Prime or OpenSesame; Run your study in the psychophysiological laboratory; Analyse data in MATLAB by following simple steps. This textbook follows a unique approach by guiding you through a single EEG study, each part introducing the relevant core knowledge and commonly available software. Practical exercises help you master the skills to independently implement every aspect of an experiment, from setting up the lab to analysing the data. Suitable for developing both basic levels of skill for undergraduates as well as advancing towards a stronger command of analysis and understanding at postgraduate level. Michiel Spape is a Lecturer and Researcher in Psychology at the University of Helsinki.

Through a multi-methodology approach, Principles and Methods of Social Research, Fourth Edition covers the latest research techniques and designs and guides readers toward the design and conduct of social research from the ground up. Applauded for its comprehensive coverage, the breadth and depth of content of this new edition is unparalleled. Explained with updated applied examples useful to the social, behavioral, educational, and organizational sciences, the methods described are relevant to contemporary researchers. The underlying logic and mechanics of experimental, quasi-experimental, and non-experimental research strategies are discussed in detail. Introductory chapters cover topics such as validity and reliability furnish readers with a firm understanding of foundational concepts. The book has chapters dedicated to sampling, interviewing, questionnaire design, stimulus scaling, observational methods, content analysis, implicit measures, dyadic and group methods, and meta-analysis to cover these essential methodologies. Notable features include an emphasis on understanding the principles that govern the use of a method to facilitate the researcher’s choice of the best technique for a given situation; use of the laboratory experiment as a touchstone to describe and evaluate field experiments, correlational designs, quasi experiments, evaluation studies, and survey designs; and coverage of the ethics of social research including the power a researcher wields and tips on how to use it responsibly. The new edition features: Increased attention to the distinction between conceptual replication and exact replication and how each contributes to cumulative science. Updated research examples that clarify the operation of various research design operations. More learning tools including more explanation of the basic concepts, more research examples, and more tables and figures, such as additional illustrations to include internet content like social media. Extensive revisions and expansions of all chapters. A fuller discussion of the dangers of unethical treatment to research participants. Principles and Methods of Social Research, Fourth Edition is intended for graduate or advanced undergraduate courses in research methods in psychology, communication, sociology, education, public health, and marketing, and further appeals to researchers in various fields of social research, such as social psychology and communication.

Based on a collection of chapters of leading scholars in the field, the purpose of this book is to intervene in current debates on the scientific foundation of psychological theory, methodology and research practice, and to offer an in-depth, situated and contextual understanding of psychological generalization. This book aims to contribute to a theoretical and methodological vocabulary which includes the subjective dimension of human life in psychological inquiry, and roots processes of generalization in persons' common, social, cultural and material practices of everyday living. The volume is directed to students, professors, and researchers in psychology as well as to scholars in other branches of the humanities and social science where psychology and especially subjectivity, everyday practice and the development of psychological knowledge is an issue. The volume will be of particular interest to scholars in the field of cultural psychology, critical psychology, psychology of everyday life as well as psychological methodology and qualitative studies of everyday life including the various critical undergraduate, graduate, master, and PhD programs. The book will also be of special interest for scholars working in social psychology, history of psychology, general psychology, theoretical psychology, environmental psychology and political psychology.

This book provides a comprehensive introduction to psychological assessment and covers areas not typically addressed in existing test and measurements texts, such as neuropsychological assessment and the use of tests in forensics settings. The book introduces the vocabulary of the profession and the most basic mathematics of testing early as being fundamental to understanding the field. Numerous examples are drawn from tests that the authors have written or otherwise helped to develop, reflecting the authors' deep understanding of these tests and their familiarity with problems encountered in test development, use, and interpretation. Following the introduction of the basic areas of psychometrics, the book moves to areas of testing that represent various approaches to measuring different psychological constructs (memory, language, executive function, etc.), with emphasis on the complex issue of cultural bias in testing. Examples of existing tests are given throughout the book; however, this book is not designed to prepare students to go out and administer, score, and interpret specific psychological tests. Rather, the purpose of this book is to provide the foundational core of knowledge about tests, measurement, and assessment constructs, issues, and quantitative tools. Explains what constitutes a psychological test, how tests are developed, how they are best used, and how to evaluate their strengths and weaknesses; Describes areas of testing that represent different approaches to measuring different psychological constructs; Explains applications of psychological testing to issues in the courts; Addresses how test authors and publishers design and research tests to address the difficult and demanding issues of cultural differences in test performance and interpretation of test results.

The power of data drives the digital economy of the 21st century. It has been argued that data is as vital a resource as oil was during the industrial revolution. An upward trend in the number of research publications using machine learning in some of the top journals in combination with an increasing number of academic recruiters within psychology asking for Python knowledge from applicants indicates a growing demand for these skills in the market. While there are plenty of books covering data science, rarely, if ever, books in the market address the need of social science students with no computer science background. They are typically written by engineers or computer scientists for people of their discipline. As a result, often such books are filled with technical jargon and examples irrelevant to psychological studies or projects. In contrast, this book was written by a psychologist in a simple, easy-to-understand way that is brief and accessible. The aim for this book was to make the learning experience on this topic as smooth as possible for psychology students/researchers with no background in programming or data science. Completing this book will also open up an enormous amount of possibilities for quantitative researchers in psychological science, as it will enable them to explore newer types of research questions.