Advertisement
| analysis of likert scale data: A Comprehensive Guide for Design, Collection, Analysis and Presentation of Likert and Other Rating Scale Data Ajit Roy, 2020-10-13 It is observed that Researchers face a lot of difficulties in planning, design, collection, analysis and interpretation of Likert Scale data. Therefore, as an aid for the researchers it is attempted to write a book entitled 'A Comprehensive Guide for Design, Collection, Analysis and Presentation of Likert and other Rating Scale Data' on this subject with the following chapters 1. Basics of Likert Scale 2. General Issues of Likert Scaling 3. Templates for Creating Likert Scales 4. Basic Concepts of Measurement 5. Analysis of Likert Data 6. Appropriate Chart or Graph for Likert scale 7. Likert Scale Data Analysis with Statistical Software.This book discusses various efforts to identify, collect, analyse, improve, and present Likert data collected by rating scales such as Likert Scale. Most importunately the book illustrates, review, and critique several forms of collection, analysis, graphical presentation and interpretation of results from studies using rating scales. The most salient and striking features covered in this book are as followsDifferences between Likert-type or Likert scale dataLikert-type data is an ordinal data, therefore, non-parametric tests such as Mann Whitney-U test, Wilcoxon signed-rank test, Kruskal-Wallis test should be used in lieu of parametric tests.Likert scale data, on the other hand, are analysed as interval data. and analysis that can be performed includes mean for central tendency, standard deviations for variability, Pearson's r for bivariate analysis, t-test and ANOVA for comparing group means, and regression procedures for associations.For Likert-type data mode or median is used for measuring central tendency and frequencies for variability. Analysis appropriate for ordinal scale items that includes the chi-square measure of association, Kendall Tau B, and Kendall Tau C.The dispute over the use of parametric versus non-parametric methods for the analysis of Likert scale ordinal data has raged for the past eight decades is discussed fully and suggested the right one.Focuses on validity, reliability and analysis of the Likert ScalePictorial display of several ways in which statistical data may be presented pictorially such as different types of graphs and diagrams is covered.Demonstration for Calculating Descriptive Statistics, Chi-Square Goodness-of-Fit, Mann-Whitney U Test, Sign Test, Wilcoxon-Mann-Whitney test and Cronbach's alpha with examples using SPSS. |
| analysis of likert scale data: Survey Scales Robert L. Johnson, Grant B. Morgan, 2016-07-05 Synthesizing the literature from the survey and measurement fields, this book explains how to develop closed-response survey scales that will accurately capture such constructs as attitudes, beliefs, or behaviors. It provides guidelines to help applied researchers or graduate students review existing scales for possible adoption or adaptation in a study; create their own conceptual framework for a scale; write checklists, true-false variations, and Likert-style items; design response scales; examine validity and reliability; conduct a factor analysis; and document the instrument development and its technical quality. Advice is given on constructing tables and graphs to report survey scale results. Concepts and procedures are illustrated with Not This/But This examples from multiple disciplines. User-Friendly Features *End-of-chapter exercises with sample solutions, plus annotated suggestions for further reading. *Not This/But This examples of poorly written and strong survey items. *Chapter-opening overviews and within-chapter summaries. *Glossary of key concepts. *Appendix with examples of parametric and nonparametric procedures for group comparisons. |
| analysis of likert scale data: A Technique for the Measurement of Attitudes Rensis Likert, 1987 |
| analysis of likert scale data: An Introduction To the Logic of Psychological Measurement Joel Michell, 2014-02-04 This book declines to take for granted the widespread assumption that existing psychometric procedures provide scientific measurement. The currently fashionable concepts of measurement within psychology -- operationalism and representationalism -- are critically examined, and the classical view, that measurement is the assessment of quantity, is defended. Within this framework, it is shown how conjoint measurement can be used to test the hypothesis that variables are quantitative. This theme is developed in detail using familiar psychological examples, such as Thurstone's law of comparative judgment, multidimensional scaling, and Coombs' theory of unfolding. |
| analysis of likert scale data: Applied Statistics: From Bivariate Through Multivariate Techniques Rebecca M. Warner, 2013 Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions. |
| analysis of likert scale data: Data Management and Analysis Using JMP Jane E Oppenlander, Patricia Schaffer, 2017-10-17 A holistic, step-by-step approach to analyzing health care data! Written for both beginner and intermediate JMP users working in or studying health care, Data Management and Analysis Using JMP: Health Care Case Studies bridges the gap between taking traditional statistics courses and successfully applying statistical analysis in the workplace. Authors Jane Oppenlander and Patricia Schaffer begin by illustrating techniques to prepare data for analysis, followed by presenting effective methods to summarize, visualize, and analyze data. The statistical analysis methods covered in the book are the foundational techniques commonly applied to meet regulatory, operational, budgeting, and research needs in the health care field. This example-driven book shows practitioners how to solve real-world problems by using an approach that includes problem definition, data management, selecting the appropriate analysis methods, step-by-step JMP instructions, and interpreting statistical results in context. Practical strategies for selecting appropriate statistical methods, remediating data anomalies, and interpreting statistical results in the domain context are emphasized. The cases presented in Data Management and Analysis Using JMP use multiple statistical methods. A progression of methods--from univariate to multivariate--is employed, illustrating a logical approach to problem-solving. Much of the data used in these cases is open source and drawn from a variety of health care settings. The book offers a welcome guide to working professionals as well as students studying statistics in health care-related fields. |
| analysis of likert scale data: Data Theory and Dimensional Analysis William G. Jacoby, 1991 For many readers, data theory is probably unfamiliar. Data isn't usually the subject matter of theory in and of itself. However, in this volume, William Jacoby introduces a theory of data idea. It examines how real world observations are transformed into something to be analyzed that is, data. Jacoby explores some of the basic ideas of data theory, and considers their implications for research strategies in the social sciences. Like others in the series, it is reassuringly slim. It is intended for a general social science readership and is a worthwhile read even for experienced data analysts. since it draws attention not only to often overlooked assumptions, but also to often ignored analysis possibilities. --Telephone Surveys On the whole, this book contains a lot of useful information. --Journal of Classification |
| analysis of likert scale data: Analysing Quantitative Survey Data for Business and Management Students Jeremy Dawson, 2016-11-10 In Analysing Quantitative Survey Data, Jeremy Dawson introduces you to the key elements of analysing quantitative survey data using classical test theory, the measurement theory that underlies the techniques described in the book. The methodological assumptions, basic components and strengths and limitations of this analysis are explained and with the help of illustrative examples, you are guided through how to conduct the key procedures involved, including reliability analysis, exploratory and confirmatory factor analysis. Ideal for Business and Management students reading for a Master’s degree, each book in the series may also serve as reference books for doctoral students and faculty members interested in the method. Part of SAGE’s Mastering Business Research Methods series, conceived and edited by Bill Lee, Mark N. K. Saunders and Vadake K. Narayanan and designed to support researchers by providing in-depth and practical guidance on using a chosen method of data collection or analysis. |
| analysis of likert scale data: Storytelling with Data Cole Nussbaumer Knaflic, 2015-10-09 Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it! |
| analysis of likert scale data: Statistics As Principled Argument Robert P. Abelson, 2012-09-10 In this illuminating volume, Robert P. Abelson delves into the too-often dismissed problems of interpreting quantitative data and then presenting them in the context of a coherent story about one's research. Unlike too many books on statistics, this is a remarkably engaging read, filled with fascinating real-life (and real-research) examples rather than with recipes for analysis. It will be of true interest and lasting value to beginning graduate students and seasoned researchers alike. The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. Five criteria, described by the acronym MAGIC (magnitude, articulation, generality, interestingness, and credibility) are proposed as crucial features of a persuasive, principled argument. Particular statistical methods are discussed, with minimum use of formulas and heavy data sets. The ideas throughout the book revolve around elementary probability theory, t tests, and simple issues of research design. It is therefore assumed that the reader has already had some access to elementary statistics. Many examples are included to explain the connection of statistics to substantive claims about real phenomena. |
| analysis of likert scale data: Neural Approaches to Dynamics of Signal Exchanges Anna Esposito, Marcos Faundez-Zanuy, Francesco Carlo Morabito, Eros Pasero, 2019-09-18 The book presents research that contributes to the development of intelligent dialog systems to simplify diverse aspects of everyday life, such as medical diagnosis and entertainment. Covering major thematic areas: machine learning and artificial neural networks; algorithms and models; and social and biometric data for applications in human–computer interfaces, it discusses processing of audio-visual signals for the detection of user-perceived states, the latest scientific discoveries in processing verbal (lexicon, syntax, and pragmatics), auditory (voice, intonation, vocal expressions) and visual signals (gestures, body language, facial expressions), as well as algorithms for detecting communication disorders, remote health-status monitoring, sentiment and affect analysis, social behaviors and engagement. Further, it examines neural and machine learning algorithms for the implementation of advanced telecommunication systems, communication with people with special needs, emotion modulation by computer contents, advanced sensors for tracking changes in real-life and automatic systems, as well as the development of advanced human–computer interfaces. The book does not focus on solving a particular problem, but instead describes the results of research that has positive effects in different fields and applications. |
| analysis of likert scale data: Unidimensional Scaling John McIver, Edward G. Carmines, 1981 This series of methodological works provides introductory explanations and demonstrations of various data analysis techniques applicable to the social sciences. Designed for readers with a limited background in statistics or mathematics, this series aims to make the assumptions and practices of quantitative analysis more readily accessible. |
| analysis of likert scale data: The SAGE Encyclopedia of Communication Research Methods Mike Allen, 2017-04-11 Communication research is evolving and changing in a world of online journals, open-access, and new ways of obtaining data and conducting experiments via the Internet. Although there are generic encyclopedias describing basic social science research methodologies in general, until now there has been no comprehensive A-to-Z reference work exploring methods specific to communication and media studies. Our entries, authored by key figures in the field, focus on special considerations when applied specifically to communication research, accompanied by engaging examples from the literature of communication, journalism, and media studies. Entries cover every step of the research process, from the creative development of research topics and questions to literature reviews, selection of best methods (whether quantitative, qualitative, or mixed) for analyzing research results and publishing research findings, whether in traditional media or via new media outlets. In addition to expected entries covering the basics of theories and methods traditionally used in communication research, other entries discuss important trends influencing the future of that research, including contemporary practical issues students will face in communication professions, the influences of globalization on research, use of new recording technologies in fieldwork, and the challenges and opportunities related to studying online multi-media environments. Email, texting, cellphone video, and blogging are shown not only as topics of research but also as means of collecting and analyzing data. Still other entries delve into considerations of accountability, copyright, confidentiality, data ownership and security, privacy, and other aspects of conducting an ethical research program. Features: 652 signed entries are contained in an authoritative work spanning four volumes available in choice of electronic or print formats. Although organized A-to-Z, front matter includes a Reader’s Guide grouping entries thematically to help students interested in a specific aspect of communication research to more easily locate directly related entries. Back matter includes a Chronology of the development of the field of communication research; a Resource Guide to classic books, journals, and associations; a Glossary introducing the terminology of the field; and a detailed Index. Entries conclude with References/Further Readings and Cross-References to related entries to guide students further in their research journeys. The Index, Reader’s Guide themes, and Cross-References combine to provide robust search-and-browse in the e-version. |
| analysis of likert scale data: Indeterminate Likert scale: feedback based on neutrosophy, its distance measures and clustering algorithm Ilanthenral Kandasamy, W. B. Vasantha Kandasamy, Jagan M. Obbineni, Florentin Smarandache, 2020-10-01 Likert scale is the most widely used psychometric scale for obtaining feedback. The major disadvantage of Likert scale is information distortion and information loss problem that arise due to its ordinal nature and closed format. Real-world responses are mostly inconsistent, imprecise and indeterminate depending on the customers’ emotions. To capture the responses realistically, the concept of neutrosophy (study of neutralities and indeterminacy) is used. Indeterminate Likert scale based on neutrosophy is introduced in this paper. Clustering according to customer feedback is an effectiveway of classifying customers and targeting them accordingly. Clustering algorithm for feedback obtained using indeterminate Likert scaling is proposed in this paper. While dealing real-world scenarios, indeterminate Likert scaling is better in capturing the responses accurately. |
| analysis of likert scale data: Summated Rating Scale Construction Paul E. Spector, 1992 Intended for the social scientist who must develop a rating on attitudes, values and opinions, this text provides information on the construction of more effective scales. It includes information on how to validate a scale and how to develop a summated rating scale based on classical test theory. |
| analysis of likert scale data: Statistical Rethinking Richard McElreath, 2018-01-03 Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas. |
| analysis of likert scale data: Beyond ANOVA Rupert G. Miller, Jr., 1997-01-01 Renowned statistician R.G. Miller set the pace for statistics students with Beyond ANOVA: Basics of Applied Statistics. Designed to show students how to work with a set of real world data, Miller's text goes beyond any specific discipline, and considers a whole variety of techniques from ANOVA to empirical Bayes methods; the jackknife, bootstrap methods; and the James-Stein estimator. This reissue of Miller's classic book has been revised by professors at Stanford University, California. As before, one of the main strengths of Beyond ANOVA is its promotion of the use of the most straightforward data analysis methods-giving students a viable option, instead of resorting to complicated and unnecessary tests. Assuming a basic background in statistics, Beyond ANOVA is written for undergraduates and graduate statistics students. Its approach will also be valued by biologists, social scientists, engineers, and anyone who may wish to handle their own data analysis. |
| analysis of likert scale data: Statistical Modeling for Management Graeme D Hutcheson, Luiz Moutinho, 2008-02-12 Bringing to life the most widely used quantitative measurements and statistical techniques in marketing, this book is packed with user-friendly descriptions, examples and study applications. The process of making marketing decisions is frequently dependent on quantitative analysis and the use of specific statistical tools and techniques which can be tailored and adapted to solve particular marketing problems. Any student hoping to enter the world of marketing will need to show that they understand and have mastered these techniques. A bank of downloadable data sets to compliment the tables provided in the textbook are provided free for you. |
| analysis of likert scale data: Grit Angela Duckworth, 2016-05-03 In this instant New York Times bestseller, Angela Duckworth shows anyone striving to succeed that the secret to outstanding achievement is not talent, but a special blend of passion and persistence she calls “grit.” “Inspiration for non-geniuses everywhere” (People). The daughter of a scientist who frequently noted her lack of “genius,” Angela Duckworth is now a celebrated researcher and professor. It was her early eye-opening stints in teaching, business consulting, and neuroscience that led to her hypothesis about what really drives success: not genius, but a unique combination of passion and long-term perseverance. In Grit, she takes us into the field to visit cadets struggling through their first days at West Point, teachers working in some of the toughest schools, and young finalists in the National Spelling Bee. She also mines fascinating insights from history and shows what can be gleaned from modern experiments in peak performance. Finally, she shares what she’s learned from interviewing dozens of high achievers—from JP Morgan CEO Jamie Dimon to New Yorker cartoon editor Bob Mankoff to Seattle Seahawks Coach Pete Carroll. “Duckworth’s ideas about the cultivation of tenacity have clearly changed some lives for the better” (The New York Times Book Review). Among Grit’s most valuable insights: any effort you make ultimately counts twice toward your goal; grit can be learned, regardless of IQ or circumstances; when it comes to child-rearing, neither a warm embrace nor high standards will work by themselves; how to trigger lifelong interest; the magic of the Hard Thing Rule; and so much more. Winningly personal, insightful, and even life-changing, Grit is a book about what goes through your head when you fall down, and how that—not talent or luck—makes all the difference. This is “a fascinating tour of the psychological research on success” (The Wall Street Journal). |
| analysis of likert scale data: Proceedings of 2019 Chinese Intelligent Automation Conference Zhidong Deng, 2019-08-08 The proceedings present selected research papers from the CIAC2019, held in Jiangsu, China on September 20-22, 2019. It covers a wide range of topics including intelligent control, robotics, artificial intelligence, pattern recognition, unmanned systems, IoT and machine learning. It includes original research and the latest advances in the field of intelligent automation. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in this field. |
| analysis of likert scale data: Designing and Doing Survey Research Lesley Andres, 2012-03-22 Designing and Doing Survey Research is an introduction to the processes and methods of planning and conducting survey research in the real world. Taking a mixed method approach throughout, the book provides step-by-step guidance on: • Designing your research • Ethical issues • Developing your survey questions • Sampling • Budgeting, scheduling and managing your time • Administering your survey • Preparing for data analysis With a focus on the impact of new technologies, this book provides a cutting-edge look at how survey research is conducted today as well as the challenges survey researchers face. Packed full of international examples from various social science disciplines, the book is ideal for students and researchers new to survey research. |
| analysis of likert scale data: The Cult of Statistical Significance Stephen Thomas Ziliak, Deirdre Nansen McCloskey, 2008-02-19 How the most important statistical method used in many of the sciences doesn't pass the test for basic common sense |
| analysis of likert scale data: A Step-by-Step Approach to Using SAS for Univariate & Multivariate Statistics Norm O'Rourke, Larry Hatcher, Edward J. Stepanski, 2005 Providing practice data inspired by actual studies, this book explains how to choose the right statistic, understand the assumptions underlying the procedure, prepare an SAS program for an analysis, interpret the output, and summarize the analysis and results according to the format prescribed in the Publication Manual of the American Psychological Association. |
| analysis of likert scale data: Conducting Online Surveys Valerie M. Sue, Lois A. Ritter, 2012 This book addresses the needs of researchers who want to conduct surveys online. Issues discussed include sampling from online populations, developing online and mobile questionnaires, and administering electronic surveys, are unique to digital surveys. Others, like creating reliable and valid survey questions, data analysis strategies, and writing the survey report, are common to all survey environments. This single resource captures the particulars of conducting digital surveys from start to finish |
| analysis of likert scale data: Longitudinal Data Analysis Garrett Fitzmaurice, Marie Davidian, Geert Verbeke, Geert Molenberghs, 2008-08-11 Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory |
| analysis of likert scale data: Social Science Research Anol Bhattacherjee, 2012-04-01 This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages. |
| analysis of likert scale data: OECD Guidelines on Measuring Subjective Well-being OECD, 2013-03-20 These Guidelines represent the first attempt to provide international recommendations on collecting, publishing, and analysing subjective well-being data. |
| analysis of likert scale data: Illustrating Statistical Procedures: Finding Meaning in Quantitative Data Ray W. Cooksey, 2020-05-14 This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them. This book provides a comprehensive overview of this important research skill domain with an emphasis on visual support for learning and better understanding. The primary focus is on fundamental concepts, procedures and interpretations of statistical analyses within a single broad illustrative research context. The book covers a wide range of descriptive, correlational and inferential statistical procedures as well as more advanced procedures not typically covered in introductory and intermediate statistical texts. It is an ideal reference for postgraduate students as well as for researchers seeking to broaden their conceptual exposure to what is possible in statistical analysis. |
| analysis of likert scale data: Encyclopedia of Survey Research Methods Paul J. Lavrakas, 2008-09-12 To the uninformed, surveys appear to be an easy type of research to design and conduct, but when students and professionals delve deeper, they encounter the vast complexities that the range and practice of survey methods present. To complicate matters, technology has rapidly affected the way surveys can be conducted; today, surveys are conducted via cell phone, the Internet, email, interactive voice response, and other technology-based modes. Thus, students, researchers, and professionals need both a comprehensive understanding of these complexities and a revised set of tools to meet the challenges. In conjunction with top survey researchers around the world and with Nielsen Media Research serving as the corporate sponsor, the Encyclopedia of Survey Research Methods presents state-of-the-art information and methodological examples from the field of survey research. Although there are other how-to guides and references texts on survey research, none is as comprehensive as this Encyclopedia, and none presents the material in such a focused and approachable manner. With more than 600 entries, this resource uses a Total Survey Error perspective that considers all aspects of possible survey error from a cost-benefit standpoint. Key Features Covers all major facets of survey research methodology, from selecting the sample design and the sampling frame, designing and pretesting the questionnaire, data collection, and data coding, to the thorny issues surrounding diminishing response rates, confidentiality, privacy, informed consent and other ethical issues, data weighting, and data analyses Presents a Reader′s Guide to organize entries around themes or specific topics and easily guide users to areas of interest Offers cross-referenced terms, a brief listing of Further Readings, and stable Web site URLs following most entries The Encyclopedia of Survey Research Methods is specifically written to appeal to beginning, intermediate, and advanced students, practitioners, researchers, consultants, and consumers of survey-based information. |
| analysis of likert scale data: Fundamental of Research Methodology and Statistics Yogesh Kumar Singh, 2006-12 The book approaches research from a perspective different from that taken in other educational research textbooks. The goal is to show educators that the application of research principles can make them more effective in their job of promoting learning. The basic point is that we do not have to stop teaching to do research; research is something we can do while teaching and if we do good research, we will do better teaching. This book includes most of the topics treated in traditional educational research books, but in a different order and with a different emphasis. The important content cons. |
| analysis of likert scale data: Analyzing Social Science Data D. A. De Vaus, 2002-09-17 Abridged Contents PART ONE: HOW TO PREPARE DATA FOR ANALYSIS\PART TWO: HOW TO PREPARE VARIABLE FOR ANALYSIS\PART THREE: HOW TO REDUCE THE AMOUNT OF DATA TO ANALYZE\PART FOUR: HOW AND WHEN TO GENERALIZE\PART FIVE: HOW TO ANALYZE A SINGLE VARIABLE\PART SIX: HOW TO ANALYZE TWO VARIABLES\PART SEVEN: HOW TO CARRY OUT MULTIVARIATE ANALYSIS |
| analysis of likert scale data: Selecting the Right Analyses for Your Data W. Paul Vogt, Dianne C. Gardner, Elaine R. Vogt, Lynne M. Haeffele, 2014-05-19 What are the most effective methods to code and analyze data for a particular study? This thoughtful and engaging book reviews the selection criteria for coding and analyzing any set of data--whether qualitative, quantitative, mixed, or visual. The authors systematically explain when to use verbal, numerical, graphic, or combined codes, and when to use qualitative, quantitative, graphic, or mixed-methods modes of analysis. Chapters on each topic are organized so that researchers can read them sequentially or can easily flip and find answers to specific questions. Nontechnical discussions of cutting-edge approaches--illustrated with real-world examples--emphasize how to choose (rather than how to implement) the various analyses. The book shows how using the right analysis methods leads to more justifiable conclusions and more persuasive presentations of research results. Useful features for teaching or self-study: *Chapter-opening preview boxes that highlight useful topics addressed. *End-of-chapter summary tables recapping the 'dos and don'ts' and advantages and disadvantages of each analytic technique. *Annotated suggestions for further reading and technical resources on each topic. Subject Areas/Keywords: analyses, coding, combined methods, data analysis, data collection, dissertation, graphical, interpretation, mixed methods, qualitative, quantitative, research analysis, research designs, research methods, social sciences, thesis, visual Audience: Researchers, instructors, and graduate students in a range of disciplines, including psychology, education, social work, sociology, health, and management; administrators and managers who need to make data-driven decisions-- |
| analysis of likert scale data: Analyzing Quantitative Data Norman Blaikie, 2003-03-06 For social researchers who need to know what procedures to use under what circumstances in practical research projects, this book does not require an indepth understanding of statistical theory. |
| analysis of likert scale data: Patient-Reported Outcomes Joseph C. Cappelleri, Kelly H. Zou, Andrew G. Bushmakin, Jose Ma. J. Alvir, Demissie Alemayehu, Tara Symonds, 2013-12-20 Advancing the development, validation, and use of patient-reported outcome (PRO) measures, Patient-Reported Outcomes: Measurement, Implementation and Interpretation helps readers develop and enrich their understanding of PRO methodology, particularly from a quantitative perspective. Designed for biopharmaceutical researchers and others in the health sciences community, it provides an up-to-date volume on conceptual and analytical issues of PRO measures. The book discusses key concepts relating to the measurement, implementation, and interpretation of PRO measures. It covers both introductory and advanced psychometric and biostatistical methods for constructing and analyzing PRO measures. The authors include many relevant real-life applications based on their extensive first-hand experiences in the pharmaceutical industry. They implement a wealth of simulated datasets to illustrate concepts and heighten understanding based on practical scenarios. For readers interested in conducting statistical analyses of PRO measures and delving more deeply into the analytic details, most chapters contain SAS code and output that illustrate the methodology. Along with providing numerous references, the book highlights current regulatory guidelines. |
| analysis of likert scale data: The Big Book of Dashboards Steve Wexler, Jeffrey Shaffer, Andy Cotgreave, 2017-04-24 The definitive reference book with real-world solutions you won't find anywhere else The Big Book of Dashboards presents a comprehensive reference for those tasked with building or overseeing the development of business dashboards. Comprising dozens of examples that address different industries and departments (healthcare, transportation, finance, human resources, marketing, customer service, sports, etc.) and different platforms (print, desktop, tablet, smartphone, and conference room display) The Big Book of Dashboards is the only book that matches great dashboards with real-world business scenarios. By organizing the book based on these scenarios and offering practical and effective visualization examples, The Big Book of Dashboards will be the trusted resource that you open when you need to build an effective business dashboard. In addition to the scenarios there's an entire section of the book that is devoted to addressing many practical and psychological factors you will encounter in your work. It's great to have theory and evidenced-based research at your disposal, but what will you do when somebody asks you to make your dashboard 'cooler' by adding packed bubbles and donut charts? The expert authors have a combined 30-plus years of hands-on experience helping people in hundreds of organizations build effective visualizations. They have fought many 'best practices' battles and having endured bring an uncommon empathy to help you, the reader of this book, survive and thrive in the data visualization world. A well-designed dashboard can point out risks, opportunities, and more; but common challenges and misconceptions can make your dashboard useless at best, and misleading at worst. The Big Book of Dashboards gives you the tools, guidance, and models you need to produce great dashboards that inform, enlighten, and engage. |
| analysis of likert scale data: Item Response Theory Ronald K. Hambleton, H. Swaminathan, 2013-11-11 In the decade of the 1970s, item response theory became the dominant topic for study by measurement specialists. But, the genesis of item response theory (IRT) can be traced back to the mid-thirties and early forties. In fact, the term Item Characteristic Curve, which is one of the main IRT concepts, can be attributed to Ledyard Tucker in 1946. Despite these early research efforts, interest in item response theory lay dormant until the late 1960s and took a backseat to the emerging development of strong true score theory. While true score theory developed rapidly and drew the attention of leading psychometricians, the problems and weaknesses inherent in its formulation began to raise concerns. Such problems as the lack of invariance of item parameters across examinee groups, and the inadequacy of classical test procedures to detect item bias or to provide a sound basis for measurement in tailored testing, gave rise to a resurgence of interest in item response theory. Impetus for the development of item response theory as we now know it was provided by Frederic M. Lord through his pioneering works (Lord, 1952; 1953a, 1953b). The progress in the fifties was painstakingly slow due to the mathematical complexity of the topic and the nonexistence of computer programs. |
| analysis of likert scale data: The Statistical Analysis of Categorical Data Erling B. Andersen, 2012-12-06 The aim of this book is to give an up to date account of the most commonly uses statist i cal models for categoriCal data. The emphasis is on the connection between theory and appIications to real data sets. The book only covers models for categorical data. Various n:t0dels for mixed continuous and categorical data are thus excluded. The book is written as a textbook, although many methods and results are quite recent. This should imply, that the book can be used for a graduate course in categorical data analysis. With this aim in mind chapters 3 to 12 are concluded with a set of exer eises. In many cases, the data sets are those data sets, which were not included in the examples of the book, although they at one point in time were regarded as potential can didates for an example. A certain amount of general knowledge of statistical theory is necessary to fully benefit from the book. A summary of the basic statistical concepts deemed necessary pre requisites is given in chapter 2. The mathematical level is only moderately high, but the account in chapter 3 of basic properties of exponential families and the parametric multinomial distribution is made as mathematical preeise as possible without going into mathematical details and leaving out most proofs. |
| analysis of likert scale data: Research Methodology and Data Analysis Second Edition Zainudin Awang, 2012 This book provides proper direction in doing research especially towards the understanding of research objectives, and research hypotheses. The book also guides in research methodology such as the methods of designing a questionnaire, methods of sampling, methods of data collection and methods of data analysis. The data analysis covers data mining, descriptive analysis, factor analysis, and reliability analysis. Besides this, the book assesses the normality distribution of data since this is crucial in determining the types of statistical analysis to be employed. More importantly, the book offers guide in analysing the correlational effects, causal effects, mediator effects and also the moderator effect among variables in a model. |
| analysis of likert scale data: Soft Computing Applications for Group Decision-making and Consensus Modeling Mikael Collan, Janusz Kacprzyk, 2017-06-30 This book offers a concise introduction and comprehensive overview of the state of the art in the field of decision-making and consensus modeling, with a special emphasis on fuzzy methods. It consists of a collection of authoritative contributions reporting on the decision-making process from different perspectives: from psychology to social and political sciences, from decision sciences to data mining, and from computational sciences in general, to artificial and computational intelligence and systems. Written as a homage to Mario Fedrizzi for his scholarly achievements, creative ideas and long lasting services to different scientific communities, it introduces key theoretical concepts, describes new models and methods, and discusses a range of promising real-world applications in the field of decision-making science. It is a timely reference guide and a source of inspiration for advanced students and researchers |
| analysis of likert scale data: Scale Development Robert F. DeVellis, 2016-03-30 In the Fourth Edition of Scale Development, Robert F. DeVellis demystifies measurement by emphasizing a logical rather than strictly mathematical understanding of concepts. The text supports readers in comprehending newer approaches to measurement, comparing them to classical approaches, and grasping more clearly the relative merits of each. This edition addresses new topics pertinent to modern measurement approaches and includes additional exercises and topics for class discussion. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more. |
analysis 与 analyses 有什么区别? - 知乎
也就是说，当analysis 在具体语境中表示抽象概念时，它就成为了不可数名词，本身就没有analyses这个复数形式，二者怎么能互换呢？ 当analysis 在具体语境中表示可数名词概念时（ …
Geopolitics: Geopolitical news, analysis, & discussion - Reddit
Geopolitics is focused on the relationship between politics and territory. Through geopolitics we attempt to analyze and predict the actions and decisions of nations, or other forms of political …
r/StockMarket - Reddit's Front Page of the Stock Market
Welcome to /r/StockMarket! Our objective is to provide short and mid term trade ideas, market analysis & commentary for active traders and investors. Posts about equities, options, forex, …
Alternate Recipes In-Depth Analysis - An Objective Follow-up
Sep 14, 2021 · This analysis in the spreadsheet is completely objective. The post illustrates only one of the many playing styles, the criteria of which are clearly defined in the post - a middle of …
What is the limit for number of files and data analysis for ... - Reddit
Jun 19, 2024 · Number of Files: You can upload up to 25 files concurrently for analysis. This includes a mix of different types, such as documents, images, and spreadsheets. Data …
为什么很多人认为TPAMI是人工智能所有领域的顶刊？ - 知乎
Dec 15, 2024 · TPAMI全称是IEEE Transactions on Pattern Analysis and Machine Intelligence，从名字就能看出来，它关注的是"模式分析"和"机器智能"这两个大方向。这两个方向恰恰是人工 …
The UFO reddit
Aug 31, 2022 · We have declassified documents about anomalous incidents that directly conflict the new AARO report to a point it makes me wonder what they are even doing.
origin怎么进行线性拟合 求步骤和过程？ - 知乎
在 Graph 1 为当前激活窗口时，点击 Origin 菜单栏上的 Analysis ——> Fitting ——> Linear Fit ——> Open Dialog。直接点 OK 就可以了。 完成之后，你会在 Graph 1 中看到一条红色的直线 …
X射线光电子能谱（XPS）
X射线光电子能谱（XPS）是一种用于分析材料表面化学成分和电子状态的先进技术。
Do AI-Based Trading Bots Actually Work for Consistent Profit?
Sep 18, 2023 · Statisitical analysis of human trends in sentiment seems to be a reasonable approach to anticipating changes in sentiment which drives some amount of trading behaviors. …
analysis 与 analyses 有什么区别? - 知乎
也就是说，当analysis 在具体语境中表示抽象概念时，它就成为了不可数名词，本身就没有analyses这个复数形式，二者怎么能互换呢？ 当analysis 在具体语境中表示可数名词概念时（ …
Geopolitics: Geopolitical news, analysis, & discussion - Reddit
Geopolitics is focused on the relationship between politics and territory. Through geopolitics we attempt to analyze and predict the actions and decisions of nations, or other forms of political …
r/StockMarket - Reddit's Front Page of the Stock Market
Welcome to /r/StockMarket! Our objective is to provide short and mid term trade ideas, market analysis & commentary for active traders and investors. Posts about equities, options, forex, …
Alternate Recipes In-Depth Analysis - An Objective Follow-up
Sep 14, 2021 · This analysis in the spreadsheet is completely objective. The post illustrates only one of the many playing styles, the criteria of which are clearly defined in the post - a middle of …
What is the limit for number of files and data analysis for ... - Reddit
Jun 19, 2024 · Number of Files: You can upload up to 25 files concurrently for analysis. This includes a mix of different types, such as documents, images, and spreadsheets. Data …
为什么很多人认为TPAMI是人工智能所有领域的顶刊？ - 知乎
Dec 15, 2024 · TPAMI全称是IEEE Transactions on Pattern Analysis and Machine Intelligence，从名字就能看出来，它关注的是"模式分析"和"机器智能"这两个大方向。这两个 …
The UFO reddit
Aug 31, 2022 · We have declassified documents about anomalous incidents that directly conflict the new AARO report to a point it makes me wonder what they are even doing.
origin怎么进行线性拟合 求步骤和过程？ - 知乎
在 Graph 1 为当前激活窗口时，点击 Origin 菜单栏上的 Analysis ——> Fitting ——> Linear Fit ——> Open Dialog。直接点 OK 就可以了。 完成之后，你会在 Graph 1 中看到一条红色的直线 …
X射线光电子能谱（XPS）
X射线光电子能谱（XPS）是一种用于分析材料表面化学成分和电子状态的先进技术。
Do AI-Based Trading Bots Actually Work for Consistent Profit?
Sep 18, 2023 · Statisitical analysis of human trends in sentiment seems to be a reasonable approach to anticipating changes in sentiment which drives some amount of trading behaviors. …
