Sebanyak 3275 item atau buku ditemukan

Research Methodology in Management and Industrial Engineering

This book deals with methodological issues in the field of management and industrial engineering. It aims to answer the following questions that researchers face every time they look to develop their research: How can we design a research project? What kind of paradigm should we follow? Should we develop a qualitative / phenomenological research or a quantitative / positivistic one? What technics for data collections can we use? Should we use the entire population or a sample? What kind of sampling techniques can we have? This book provides discussion and the exchange of information on principles, strategies, models, techniques, applications and methodological options possible to develop in research in management and industrial engineering. It communicates the latest developments and thinking on the research methodologies subject in the different areas, worldwide. It seeks cultural and geographic diversity in studies highlighting research methodologies that can be used in these different study areas. This book has a special interest in research on important issues that transcend the boundaries of single academic subjects. It presents contributions that challenge the paradigms and assumptions of individual disciplines or functions, with chapters grounded in conceptual and / or empirical literature. The main aim of this book is to provide a channel of communication to disseminate knowledge between academics and researchers, with a special focus on the management and industrial engineering fields. This book can serve as a useful reference for academics, researchers, managers, engineers, and other professionals in related matters with research methodologies. Contributors have identified the theoretical and practical implications of their methodological options to the development and improvement of their different study and research areas.

This book deals with methodological issues in the field of management and industrial engineering.

Exploratory Data Analysis in Empirical Research

Proceedings of the 25th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Munich, March 14–16, 2001

This volume presents a selection of new methods and approaches in the field of Exploratory Data Analysis. The reader will find numerous ideas and examples for cross disciplinary applications of classification and data analysis methods in fields such as data and web mining, medicine and biological sciences as well as marketing, finance and management sciences.

This volume presents a selection of new methods and approaches in the field of Exploratory Data Analysis.

An Introduction to Statistics and Data Analysis Using Stata®

From Research Design to Final Report

An Introduction to Statistics and Data Analysis Using Stata® by Lisa Daniels and Nicholas Minot provides a step-by-step introduction for statistics, data analysis, or research methods classes with Stata. Concise descriptions emphasize the concepts behind statistics for students rather than the derivations of the formulas. With real-world examples from a variety of disciplines and extensive detail on the commands in Stata, this text provides an integrated approach to research design, statistical analysis, and report writing for social science students.

With real-world examples from a variety of disciplines and extensive detail on the commands in Stata, this text provides an integrated approach to research design, statistical analysis, and report writing for social science students.

Research Design and Statistical Analysis

Third Edition

Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data. The book’s goal is to provide a strong conceptual foundation to enable readers to generalize concepts to new research situations. Emphasis is placed on the underlying logic and assumptions of the analysis and what it tells the researcher, the limitations of the analysis, and the consequences of violating assumptions. Sampling, design efficiency, and statistical models are emphasized throughout. As per APA recommendations, emphasis is also placed on data exploration, effect size measures, confidence intervals, and using power analyses to determine sample size. "Real-world" data sets are used to illustrate data exploration, analysis, and interpretation. The book offers a rare blend of the underlying statistical assumptions, the consequences of their violations, and practical advice on dealing with them. Changes in the New Edition: Each section of the book concludes with a chapter that provides an integrated example of how to apply the concepts and procedures covered in the chapters of the section. In addition, the advantages and disadvantages of alternative designs are discussed. A new chapter (1) reviews the major steps in planning and executing a study, and the implications of those decisions for subsequent analyses and interpretations. A new chapter (13) compares experimental designs to reinforce the connection between design and analysis and to help readers achieve the most efficient research study. A new chapter (27) on common errors in data analysis and interpretation. Increased emphasis on power analyses to determine sample size using the G*Power 3 program. Many new data sets and problems. More examples of the use of SPSS (PASW) Version 17, although the analyses exemplified are readily carried out by any of the major statistical software packages. A companion website with the data used in the text and the exercises in SPSS and Excel formats; SPSS syntax files for performing analyses; extra material on logistic and multiple regression; technical notes that develop some of the formulas; and a solutions manual and the text figures and tables for instructors only. Part 1 reviews research planning, data exploration, and basic concepts in statistics including sampling, hypothesis testing, measures of effect size, estimators, and confidence intervals. Part 2 presents between-subject designs. The statistical models underlying the analysis of variance for these designs are emphasized, along with the role of expected mean squares in estimating effects of variables, the interpretation of nteractions, and procedures for testing contrasts and controlling error rates. Part 3 focuses on repeated-measures designs and considers the advantages and disadvantages of different mixed designs. Part 4 presents detailed coverage of correlation and bivariate and multiple regression with emphasis on interpretation and common errors, and discusses the usefulness and limitations of these procedures as tools for prediction and for developing theory. This is one of the few books with coverage sufficient for a 2-semester course sequence in experimental design and statistics as taught in psychology, education, and other behavioral, social, and health sciences. Incorporating the analyses of both experimental and observational data provides continuity of concepts and notation. Prerequisites include courses on basic research methods and statistics. The book is also an excellent resource for practicing researchers.

This is one of the few books with coverage sufficient for a 2-semester course sequence in experimental design and statistics as taught in psychology, education, and other behavioral, social, and health sciences.

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.

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.

Nursing Research Using Data Analysis

Qualitative Designs and Methods in Nursing

Nursing Research Using Data Analysis: Qualitative Designs and Methods in Nursing is one book in a series of seven volumes that presents concise, how-to guides to conducting qualitative research -- for novice researchers and specialists seeking to develop or expand their competency, health institution research divisions, in-service educators and students, and graduate nursing educators and students.

Nursing Research Using Data Analysis: Qualitative Designs and Methods in Nursing is one book in a series of seven volumes that presents concise, how-to guides to conducting qualitative research -- for novice researchers and specialists ...