Sebanyak 21321 item atau buku ditemukan

Statistics

A Tool for Social Research and Data Analysis

Extremely student friendly, Healey's STATISTICS: A TOOL FOR SOCIAL RESEARCH AND DATA ANALYSIS, 11e, equips you with a solid understanding of statistical fundamentals and their practical application to current social issues -- no advanced math knowledge required. The text breaks down even the most complex material to help you master key concepts and develop the skills you need as a professional in a social science field -- or simply to become a "statistically literate" consumer of social research. Everyday examples illustrate that statistics are not just abstract mathematical constructs, but they have practical value in government, education, business, media, politics, sports and more. Research examples in every chapter include the same "real data" used by professionals across various fields to make evidence-based decisions. Also available: MindTap digital learning solution.

The text breaks down even the most complex material to help you master key concepts and develop the skills you need to succeed as a professional in a social science field -- or simply to become a statistically literate consumer of social ...

Advanced Statistics in Research

Reading, Understanding, and Writing Up Data Analysis Results

"Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results" is the simple, nontechnical introduction to the most complex multivariate statistics presented in empirical research articles. "wwwStatsInResearch.com, " is a companion website that provides free sample chapters, exercises, and PowerPoint slides for students and teachers. A free 600-item test bank is available to instructors. "Advanced Statistics in Research" does not show how to "perform" statistical procedures--it shows how to read, understand, and interpret them, as they are typically presented in journal articles and research reports. It demystifies the sophisticated statistics that stop most readers cold: multiple regression, logistic regression, discriminant analysis, ANOVA, ANCOVA, MANOVA, factor analysis, path analysis, structural equation modeling, meta-analysis--and more. "Advanced Statistics in Research" assumes that you have never had a course in statistics. It begins at the beginning, with research design, central tendency, variability, z scores, and the normal curve. You will learn (or re-learn) the big-three results that are common to most procedures: statistical significance, confidence intervals, and effect size. Step-by-step, each chapter gently builds on earlier concepts. Matrix algebra is avoided, and complex topics are explained using simple, easy-to-understand examples. "Need help writing up your results?" Advanced Statistics in Research shows how data-analysis results can be summarized in text, tables, and figures according to APA format. You will see how to present the basics (e.g., means and standard deviations) as well as the advanced (e.g., factor patterns, post-hoc tests, path models, and more). "Advanced Statistics in Research" is appropriate as a textbook for graduate students and upper-level undergraduates (see supplementary materials at StatsInResearch.com). It also serves as a handy shelf reference for investigators and all consumers of research.

Advanced Statistics in Research: Reading, Understanding and Writing Up Data Anaylsis Results; makes multivariate statistics accessible to all readers--including those with little training in research or data analysis; Advanced Statistics in ...

Qualitative Research Using R: A Systematic Approach

This book highlights the rise of the Strauss-Corbin-Gioia (SCG) methodology as an important paradigm in qualitative research in the social sciences, and demonstrates how the SCG methodology can be operationalized and enhanced using RQDA. It also provides a technical and methodological review of RQDA as a new CAQDAS tool. Covering various techniques, it offers methodological guidance on how to connect CAQDAS tool with accepted paradigms, particularly the SCG methodology, to produce high- quality qualitative research and includes step-by-step instructions on using RQDA under the SCG qualitative research paradigm. Lastly, it comprehensively discusses methodological issues in qualitative research. This book is useful for qualitative scholars, PhD/postdoctoral students and students taking qualitative methodology courses in the broader social sciences, and those who are familiar with programming languages and wish to cross over to qualitative data analysis. "At long last! We now have a qualitative data-analysis approach that enhances the use of a systematic methodology for conducting qualitative research. Chandra and Shang should be applauded for making our research lives a lot easier. And to top it all off, it’s free." Dennis Gioia, Robert & Judith Auritt Klein Professor of Management, Smeal College of Business at Penn State University, USA “While we have a growing library of books on qualitative data analysis, this new volume provides a much needed new perspective. By combining a sophisticated understanding of qualitative research with an impressive command of R, the authors provide an important new toolkit for qualitative researchers that will improve the depth and rigor of their data analysis. And given that R is open source and freely available, their approach solves the all too common problem of access that arises from the prohibitive cost of more traditional qualitative data analysis software. Students and seasoned researchers alike should take note!” Nelson Phillips, Abu Dhabi Chamber Chair in Strategy and Innovation, Imperial College Business School, United Kingdom "This helpful book does what it sets out to do: offers a guide for systematizing and building a trail of evidence by integrating RQDA with the Gioia approach to analyzing inductive data. The authors provide easy-to-follow yet detailed instructions underpinned by sound logic, explanations and examples. The book makes me want to go back to my old data and start over!" Nicole Coviello, Lazaridis Research Professor, Wilfrid Laurier University, Canada "Qualitative Research Using R: A Systematic Approach guides aspiring researchers through the process of conducting a qualitative study with the assistance of the R programming language. It is the only textbook that offers “click‐by-click” instruction in how to use RQDA software to carry out analysis. This book will undoubtedly serve as a useful resource for those interested in learning more about R as applied to qualitative or mixed methods data analysis. Helpful as well is the six‐step procedure for carrying out a grounded‐theory type study (the “Gioia approach”) with the support of RQDA software, making it a comprehensive resource for those interested in innovative qualitative methods and uses of CAQDAS tools." Trena M. Paulus, Professor of Education, University of Georgia, USA

This book highlights the rise of the Strauss-Corbin-Gioia (SCG) methodology as an important paradigm in qualitative research in the social sciences, and demonstrates how the SCG methodology can be operationalized and enhanced using RQDA.

Data Analysis, Interpretation, and Theory in Literacy Studies Research

A How-To Guide

This research guide addresses the difficulties novice and early career researchers often have with understanding how theory, data analysis and interpretation of findings "hang together" in a well-designed and theorized qualitative research investigation, as well as learning how to draw on such understanding to conduct rigorous data analysis and interpretation of their analytic results. Books that describe data analysis approaches and methods often fail to address the question of how to decide which ones are most appropriate for a particular kind of study, and why they are the best options. This book seeks to clarify these issues in a distinctive way. Chapter authors draw on a successful study they have undertaken and spell out their "problem area," research questions, and theoretical framing, carefully explaining their choices and decisions. They then show in detail how they analyzed their data, and why they took this approach. Finally, they demonstrate how they "translated" or interpreted the results of their analysis, to make them meaningful in research terms. Approaches include interactional sociolinguistics, microethnographic discourse analysis, multimodal analysis, iterative coding, conversation analysis, and multimediated discourse analysis, among others. This book will appeal to beginning researchers and to literacy researchers responsible for teaching qualitative literacy studies research design at undergraduate and graduate levels. Perfect for courses such as: Literacy Research Seminar | Introduction to Qualitative Research | Advanced Research Methods | Studying New Literacies and Media | Research Perspectives in Literacy | Discourse Analysis | Advanced Qualitative Data Analysis | Sociolinguistic Analysis | Classroom Language Research

This book will appeal to beginning researchers and to literacy researchers responsible for teaching qualitative literacy studies research design at undergraduate and graduate levels.

Data Analysis for Research Designs

Data Analysis for Research Designs covers the analytical techniques for the analysis of variance (ANOVA) and multiple regression/correlation (MRC), emphasizing single-degree-of-freedom comparisons so that students focus on clear research planning. This text is designed for advanced undergraduates and graduate students of the behavioral and social sciences who have an understanding of algebra and statistics.

This text is designed for advanced undergraduates and graduate students of the behavioral and social sciences who have an understanding of algebra and statistics.

Research Methods & Data Analysis for Multicultural Social Work and Human Services

Research Methods & Data Analysis for Multicultural Social Work and Human Services introduces research methodology to social work students and practitioners. It provides hands-on examples of how to conduct data analysis in SPSS and Stata. It equips readers with the skills needed to become critical research consumers and to engage in agency-based research and evaluation. The text teaches students how to collect appropriate data and analyze data that is suitable for each type of research design. It prepares them to conduct applied social science research in a variety of fields, such as health and mental health, ethnic studies, acculturation, family violence, LGBT studies, and more. Topics addressed include the process of research, ethical issues, the validity and reliability of research instruments, design types, and relevant statistical tools. Research Methods & Data Analysis for Multicultural Social Work and Human Services provides a solid foundation and knowledge base for students and researchers. It is an excellent resource for undergraduate and graduate level research methods and design classes and courses on research and statistics in social work. Thanh V. Tran holds a Ph.D. and a master of science degree in social work from the School of Social Work at the University of Texas, Arlington. Dr. Tran is a professor in the Boston College School of Social Work in Chestnut Hill, Massachusetts. Ce Shen earned a Ph.D. in sociology at Boston College in Chestnut Hill and is now an associate professor in the college's School of Social Work. Siyon Rhee earned a Ph.D. at the School of Social Welfare, University of California, Los Angeles. Dr. Rhee teaches in the School of Social Work at California State University, Los Angeles.

The text teaches students how to collect appropriate data and analyze data that is suitable for each type of research design.

Data Analysis for Social Science and Marketing Research Using Python

A Non Programmer's Guide

The book is written for researchers in social science and marketing field, especially for those with little or no knowledge in computer programming. Data analytics has become part and parcel in the contemporary technologically fast paced world. We have amazing tools and software that allow us to analyse data available in various formats. However, most of the popular paid software and packages for data analysis is not affordable or not even accessible for the students, researchers. This is true in the case of many NGOs and agencies how are involved in community based research in developing countries. We have popular open source platforms and tools such as R and Python for data analysis. This book makes use of Python because of its simplicity, adaptability, broader scope and greater potential in advanced data mining and text mining contexts. We found it as a need to educate and train the researchers from social science and marketing research background, so that they could make use of Python, a promising tool to meet simple to extremely complex data analyses needs free of cost. The learnings from this book will not only help them in doing their conventional data analyses but also enable them to pursue advanced knowledge in machine learning algorithms, text analytics and other new generation techniques with the support of freely accessible open source platforms. Since the objective of the book is to educate the researchers with no programming background, we have made every effort to give hands-on experience in learning some basic coding in Python, which is sufficient for the readers to follow the book. The step-by-step procedure to do various data processing and analysis described in this book will make it easy for the users. Apart from that, we have tried our level best to give explanations on specific codes and how they perform to get us the desired output. We also request you to give you valuable comments and suggestions on the book, via our blog, so that we could improve the same in the upcoming volumes. We commit ourselves to providing explanations to the readers' questions related to the codes and analysis provided in this book. The book specifically deals with data sets of row and column format, as the general format commonly used in social science research, which most of the researchers are familiar with. So we do not work with arrays and dictionaries, except in one or two occasions (only to make you familiar with that) instead prefer to make use of Excel data and pandas data frame. The book consists of thirteen chapters. The first chapter gives an introduction to Python and its relevance and scope in contemporary data analysis contexts. Ch. 2 teaches the basics and Python coding, Ch. 3-7, provide a step-by-step narration of how to enter data, process it, preliminary analysis and data cleaning with the help of Python, Ch.8-9, present data visualizations and narration techniques using Python; Ch.10.demonstrate how Python can use for statistical analysis. The remaining chapters are focusing on giving more real life situations in data analysis and the practical solutions to handle them. The exercises provided in the book are similar to real analysis situations, and that will help the reader for an easy transition to the data analyst jobs. The authors have taken utmost care identifying and providing solutions to all practical difficulties the readers may face while using Python for data analysis purpose. The authors have developed a series of codes and have incorporated them to make data processing and analysis convenient and easy for the researchers. The self-learning materials given in this book will help social science and marketing researchers to deepen their understanding of various steps in data processing and analyses and to gain advanced skills in using Python for this purpose.

This is true in the case of many NGOs and agencies how are involved in community based research in developing countries. We have popular open source platforms and tools such as R and Python for data analysis.

Qualitative Research: Data Collection and Data Analysis Techniques -2nd Edition (UUM Press)

Qualitative Research: Data Collection & Data Analysis Techniques (2nd Edition) has been systematically revised with additional content, more in-depth explanations, and latest references to enhance the knowledge and skills required for those interested in conducting qualitative research. The reader-friendly organisation and writing style of this edition provides guaranteed accessibility to a wide array of readers ranging from established scholars to novice researchers and undergraduates. Each chapter in this edition is set to provide a clear, contextualised and comprehensive coverage of the main qualitative research methods (interviews, focus groups, observations, diary studies, archival document analysis, and content analysis) aimed at equipping readers with a thorough understanding of the design, procedures and skills to effectively undertake qualitative research. At the same time, the authors have anticipated major concerns such as ethical issues that qualitative researchers often face and addressed them in the various chapters. This effort has been made possible through the collaboration involving notable qualitative research scholars from different tertiary institutions – Assoc. Prof. Dr. Puvensvary Muthiah (ELT Consultant), Dr. R. Sivabala Naidu (Taylor’s College), Assoc. Prof. Dr. Mastura Badzis (International Islamic University Malaysia), Dr. Radziah Abdul Rahim (formerly attached to National Defense University of Malaysia), Dr. Noor Fadhilah Mat Nayan (University of Reading), and Assoc. Prof. Noor Hashima Abd Aziz (Universiti Utara Malaysia).

Each chapter in this edition is set to provide a clear, contextualised and comprehensive coverage of the main qualitative research methods (interviews, focus groups, observations, diary studies, archival document analysis, and content ...

Understanding Criminological Research

A Guide to Data Analysis

Criminological research lies at the heart of criminological theory, influences social policy development, as well as informs criminal justice practice. The ability to collect, analyse and present empirical data is a core skill every student of criminology must learn. Written as an engaging step-by-step guide and illustrated by detailed case studies, this book guides the reader in how to analyse criminological data. Key features of the book include: o Guidance on how to identify a research topic, designing a research study, accounting for the role of the researcher and writing up and presenting research findings. o A thorough account of the development of qualitative and quantitative research methodologies and data analysis within the field of criminology. o Relevant and up-to-date case studies, drawn from internationally published criminological research sources. o Clear and accessible chapter content supported by helpful introductions, concise summaries, self-study questions and suggestions for further reading. Understanding Criminological Research: A Guide to Data Analysis in invaluable reading for both undergraduate and postgraduate students in criminology and criminal justice.

Written as an engaging step-by-step guide and illustrated by detailed case studies, this book guides the reader in how to analyse criminological data.

Qualitative Research

A Guide to Design and Implementation

"This thoroughly revised and updated classic once again presents aguide to understanding, designing and conducting a qualitativeresearch study. The fourth edition retains the reader-friendly, jargon-free style,making the book accessible to both novice and experiencedresearchers. While the book is practical guide to design andimplementation of a qualitative research study, it also helpsreaders understand the theoretical and philosophical underpinningsof this research paradigm. Drawing on the latest literature as well as both authors'experience with conducting and teaching qualitative research, thefourth edition includes new material on case study research andaction research; discussion of online data sources (video, email,skype); updated discussion of data analysis software packages anduses; new discussion of data analysis strategies, includingnarrative analysis and poetic analysis; and a section on multipleways of presenting qualitative research findings. References,examples, and quotes have all been updated throughout the book"--

No doubt this book will change the way we think about and publish qualitative research." —Leona M. English, head of publications and research, UNESCO Institute of Lifelong Learning, Hamburg