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| data analysis software for quantitative research: Quantitative Social Science Kosuke Imai, Lori D. Bougher, 2021-03-16 Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a translation of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place-- |
| data analysis software for quantitative research: A Step-by-Step Guide to Qualitative Data Coding Philip Adu, 2019-04-05 A Step-by-Step Guide to Qualitative Data Coding is a comprehensive qualitative data analysis guide. It is designed to help readers to systematically analyze qualitative data in a transparent and consistent manner, thus promoting the credibility of their findings. The book examines the art of coding data, categorizing codes, and synthesizing categories and themes. Using real data for demonstrations, it provides step-by-step instructions and illustrations for analyzing qualitative data. Some of the demonstrations include conducting manual coding using Microsoft Word and how to use qualitative data analysis software such as Dedoose, NVivo and QDA Miner Lite to analyze data. It also contains creative ways of presenting qualitative findings and provides practical examples. After reading this book, readers will be able to: Analyze qualitative data and present their findings Select an appropriate qualitative analysis tool Decide on the right qualitative coding and categorization strategies for their analysis Develop relationships among categories/themes Choose a suitable format for the presentation of the findings It is a great resource for qualitative research instructors and undergraduate and graduate students who want to gain skills in analyzing qualitative data or who plan to conduct a qualitative study. It is also useful for researchers and practitioners in the social and health sciences fields. |
| data analysis software for quantitative research: Using Stata for Quantitative Analysis Kyle C. Longest, 2014-07-02 Using Stata for Quantitative Analysis, Second Edition offers a brief, but thorough introduction to analyzing data with Stata software. It can be used as a reference for any statistics or methods course across the social, behavioral, and health sciences since these fields share a relatively similar approach to quantitative analysis. In this book, author Kyle Longest teaches the language of Stata from an intuitive perspective, furthering students’ overall retention and allowing a student with no experience in statistical software to work with data in a very short amount of time. The self-teaching style of this book enables novice Stata users to complete a basic quantitative research project from start to finish. The Second Edition covers the use of Stata 13 and can be used on its own or as a supplement to a research methods or statistics textbook. |
| data analysis software for quantitative research: Analyzing Qualitative Data with MAXQDA Udo Kuckartz, Stefan Rädiker, 2019-05-31 This book presents strategies for analyzing qualitative and mixed methods data with MAXQDA software, and provides guidance on implementing a variety of research methods and approaches, e.g. grounded theory, discourse analysis and qualitative content analysis, using the software. In addition, it explains specific topics, such as transcription, building a coding frame, visualization, analysis of videos, concept maps, group comparisons and the creation of literature reviews. The book is intended for masters and PhD students as well as researchers and practitioners dealing with qualitative data in various disciplines, including the educational and social sciences, psychology, public health, business or economics. |
| data analysis software for quantitative research: Using Software in Qualitative Research Ann Lewins, Christina Silver, 2007-05 Using Software in Qualitative Research is an essential introduction to the practice and principles of Computer Assisted Qualitative Data Analysis (CAQDAS), helping the reader choose the most appropriate package for their needs and to get the most out of the software once they are using it. This step-by-step book considers a wide range of tasks and processes, bringing them together to demystify qualitative software and encourage flexible and critical choices and uses of software in supporting analysis. The book can be read as a whole or by chapters, building on one another to provide a holistic sense of the analytic journey without advocating a particular sequential process. Accessible and comprehensive, Using Software in Qualitative Research provides a practical but analytically-grounded guide to thinking about and using software and will be an essential companion for any qualitative researcher. |
| data analysis software for quantitative research: Quantitative Data Analysis with SPSS 14, 15 and 16 Alan Bryman, Duncan Cramer, 2009 Providing a non-technical approach to quantitative data analysis and a user-friendly introduction to the widely used SPSS, this edition has been completely updated to accommodate the needs of users of SPSS releases 14, 15 and 16 (whilst still being applicable to those using earlier versions). |
| data analysis software for quantitative research: Qualitative Data Analysis with NVivo Patricia Bazeley, 2007-04-12 `In plain language but with very thorough detail, this book guides the researcher who really wants to use the NVivo software (and use it now) into their project. The way is lit with real-project examples, adorned with tricks and tips, but it’s a clear path to a project' - Lyn Richards, Founder and Non-Executive Director, QSR International Doing Qualitative Data Analysis with NVivo is essential reading for anyone thinking of using their computer to help analyze qualitative data. With 15 years experience in computer-assisted analysis of qualitative and mixed-mode data, Patricia Bazeley is one of the leaders in the use and teaching of NVivo software. Through this very practical book, readers are guided on how best to make use of the powerful and flexible tools offered by the latest version of NVivo as they work through each stage of their research projects. Explanations draw on examples from her own and others' projects, and are supported by the methodological literature. Researchers have different requirements and come to their data from different perspectives. This book shows how NVivo software can accommodate and assist analysis across those different perspectives and methodological approaches. It is required reading for both students and experienced researchers alike. |
| data analysis software for quantitative research: Research Methods and Data Analysis for Business Decisions James E. Sallis, Geir Gripsrud, Ulf Henning Olsson, Ragnhild Silkoset, 2021-10-30 This introductory textbook presents research methods and data analysis tools in non-technical language. It explains the research process and the basics of qualitative and quantitative data analysis, including procedures and methods, analysis, interpretation, and applications using hands-on data examples in QDA Miner Lite and IBM SPSS Statistics software. The book is divided into four parts that address study and research design; data collection, qualitative methods and surveys; statistical methods, including hypothesis testing, regression, cluster and factor analysis; and reporting. The intended audience is business and social science students learning scientific research methods, however, given its business context, the book will be equally useful for decision-makers in businesses and organizations. |
| data analysis software for quantitative research: Interpreting Quantitative Data with SPSS Rachad Antonius, 2003-01-22 This is a textbook for introductory courses in quantitative research methods across the social sciences. It offers a detailed explanation of introductory statistical techniques and presents an overview of the contexts in which they should be applied. |
| data analysis software for quantitative research: Using Microsoft Excel for Social Research Charlotte Brookfield, 2021-01-20 Full of practical advice and real-world examples, this step-by-step guide offers you an accessible introduction to doing quantitative social research using Microsoft Excel. |
| data analysis software for quantitative research: Quantitative Data Analysis Donald J. Treiman, 2014-01-30 This book is an accessible introduction to quantitative dataanalysis, concentrating on the key issues facing those new toresearch, such as how to decide which statistical procedure issuitable, and how to interpret the subsequent results. Each chapterincludes illustrative examples and a set of exercises that allowsreaders to test their understanding of the topic. The book, writtenfor graduate students in the social sciences, public health, andeducation, offers a practical approach to making sociological senseout of a body of quantitative data. The book also will be useful tomore experienced researchers who need a readily accessible handbookon quantitative methods. The author has posted stata files, updates and data sets athis websitehttp://tinyurl.com/Treiman-stata-files-data-sets. |
| data analysis software for quantitative research: Quantitative Data Analysis Willem Mertens, Amedeo Pugliese, Jan Recker, 2016-09-29 This book offers postgraduate and early career researchers in accounting and information systems a guide to choosing, executing and reporting appropriate data analysis methods to answer their research questions. It provides readers with a basic understanding of the steps that each method involves, and of the facets of the analysis that require special attention. Rather than presenting an exhaustive overview of the methods or explaining them in detail, the book serves as a starting point for developing data analysis skills: it provides hands-on guidelines for conducting the most common analyses and reporting results, and includes pointers to more extensive resources. Comprehensive yet succinct, the book is brief and written in a language that everyone can understand - from students to those employed by organizations wanting to study the context in which they work. It also serves as a refresher for researchers who have learned data analysis techniques previously but who need a reminder for the specific study they are involved in. |
| data analysis software for quantitative research: Quantitative and Statistical Research Methods William E. Martin, Krista D. Bridgmon, 2012-07-09 Quantitative and Statistical Research Methods This user-friendly textbook teaches students to understand and apply procedural steps in completing quantitative studies. It explains statistics while progressing through the steps of the hypothesis-testing process from hypothesis to results. The research problems used in the book reflect statistical applications related to interesting and important topics. In addition, the book provides a Research Analysis and Interpretation Guide to help students analyze research articles. Designed as a hands-on resource, each chapter covers a single research problem and offers directions for implementing the research method from start to finish. Readers will learn how to: Pinpoint research questions and hypotheses Identify, classify, and operationally define the study variables Choose appropriate research designs Conduct power analysis Select an appropriate statistic for the problem Use a data set Conduct data screening and analyses using SPSS Interpret the statistics Write the results related to the problem Quantitative and Statistical Research Methods allows students to immediately, independently, and successfully apply quantitative methods to their own research projects. |
| data analysis software for quantitative research: Data Analysis in Management with SPSS Software J.P. Verma, 2012-12-13 This book provides readers with a greater understanding of a variety of statistical techniques along with the procedure to use the most popular statistical software package SPSS. It strengthens the intuitive understanding of the material, thereby increasing the ability to successfully analyze data in the future. The book provides more control in the analysis of data so that readers can apply the techniques to a broader spectrum of research problems. This book focuses on providing readers with the knowledge and skills needed to carry out research in management, humanities, social and behavioural sciences by using SPSS. |
| data analysis software for quantitative research: Digital Tools for Qualitative Research Trena Paulus, Jessica N. Lester, Paul Dempster, 2013-12-30 Digital Tools for Qualitative Research shows how the research process in its entirety can be supported by technology tools in ways that can save time and add robustness and depth to qualitative work. It addresses the use of a variety of tools (many of which may already be familiar to you) to support every phase of the research process, providing practical case studies taken from real world research. The text shows you how to select and use technology tools to: engage in reflexivity collaborate with other researchers and stakeholders manage your project do your literature review generate and manage your data transcribe and analyse textual, audio and visual data and represent and share your findings. The book also considers important ethical issues surrounding the use of various technologies in each chapter. On the companion website, you′ll find lots of additional resources including video tutorials and activities. Whether you′re a novice or expert social researcher, this book will inspire you to think creatively about how to approach your research project and get the most out of the huge range of tools available to you. |
| data analysis software for quantitative research: Business Statistics For Dummies Alan Anderson, 2013-11-26 Score higher in your business statistics course? Easy. Business statistics is a common course for business majors and MBA candidates. It examines common data sets and the proper way to use such information when conducting research and producing informational reports such as profit and loss statements, customer satisfaction surveys, and peer comparisons. Business Statistics For Dummies tracks to a typical business statistics course offered at the undergraduate and graduate levels and provides clear, practical explanations of business statistical ideas, techniques, formulas, and calculations, with lots of examples that shows you how these concepts apply to the world of global business and economics. Shows you how to use statistical data to get an informed and unbiased picture of the market Serves as an excellent supplement to classroom learning Helps you score your highest in your Business Statistics course If you're studying business at the university level or you're a professional looking for a desk reference on this complicated topic, Business Statistics For Dummies has you covered. |
| data analysis software for quantitative research: Using Grounded Theory In Nursing Rita Sara Schreiber, RN, DNS, Phyllis Noerager Stern, DNS, FAAN, NAP, 2001-06-06 ìThis uniformly fine book extends and intensifies the dialogue about grounded theory and nursing.... well-designed, well-crafted, and accessible.î --Sally A. Hutchinson, PhD, RN, FAAN ì...the torch has been passed to a new generation of grounded theorists.... The editors have assembled chapters by many of the best-known scholars in North America.î --Sandra P. Thomas, PhD, RN, FAAN What is grounded theory? How is it done? When is it most appropriate to use? Grounded theory can be the research method of choice for nurses seeking to find out how people cope with existing or potential health challenges. This book offers broad coverage of method, background, philosophical roots, and new directions for grounded theory in nursing. |
| data analysis software for quantitative research: Applied Statistics Using SPSS, STATISTICA and MATLAB Joaquim P. Marques de Sá, 2013-03-09 Assuming no previous statistics education, this practical reference provides a comprehensive introduction and tutorial on the main statistical analysis topics, demonstrating their solution with the most common software package. Intended for anyone needing to apply statistical analysis to a large variety of science and enigineering problems, the book explains and shows how to use SPSS, MATLAB, STATISTICA and R for analysis such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. It concisely explains key concepts and methods, illustrated by practical examples using real data, and includes a CD-ROM with software tools and data sets used in the examples and exercises. Readers learn which software tools to apply and also gain insights into the comparative capabilities of the primary software packages. |
| data analysis software for quantitative research: The Nvivo Qualitative Project Book Patricia Bazeley, Lyn Richards, 2000-10-13 `A great basic book, which can be used by the novice qualitative researcher. The advice is friendly, almost folksy with clear conceptual explanation of how the program works. A very welcome contribution to this field' - Martha Ann Carey, Albert Einstein College of Medicine, New York `Qualitative researchers continue to be criticized because they rely too much on their own interpretations and avoid analytical and theoretical issues. This book provides ways to integrate the thinking about a project and the data you have with practical ways that the software can facilitate the process. I recommend it for both the new user as well as the experienced one' - Marilyn Lichtman, Forum for Qualitative Social Research - follow the link below to read the complete review This book invites readers to learn how to use qualitative data analysis software in the context of doing their research project. The reader follows basic steps for creating and conducting a real project with real data, using the new-generation software package, QSR NVivo. The software tools are introduced only as needed and explained in the framework of what is being asked. The reader is the craftsperson, trialling those tools in the processes of getting started, tentative interpretation, drawing links, shaping data, and seeking and establishing explanations and theories. The NVivo Qualitative Project Book allows the researcher to work through their own project, or work with data provided from a real project. The authors draw on decades of experience of research and training researchers around the world, and take the reader through each step in a style combining informality and authority, with frequent tips and reflections on what is being done. Demonstration software is provided on the enclosed CD-ROM, with data to help create (a researcher's project) a project about researchers and researching, and with multiple stages arranged sequentially in the development of a real project. As a practical tool to help researchers understand qualitative data analysis software using NVivo, and a guide through the sometimes complex processes of doing a research project, this book will be invaluable reading for researchers and students undertaking qualitative research. Pat Bazeley provides training and consulting services in research design and data analysis through her company, Research Support. Lyn Richards is Director of Research Services at Qualitative Solutions and Research, the developers of NUD·IST and NVivo software. NVivo is distributed by Scolari, SAGE Publications Software. |
| data analysis software for quantitative research: Genetic Data Analysis for Plant and Animal Breeding Fikret Isik, James Holland, Christian Maltecca, 2017-09-09 This book fills the gap between textbooks of quantitative genetic theory, and software manuals that provide details on analytical methods but little context or perspective on which methods may be most appropriate for a particular application. Accordingly this book is composed of two sections. The first section (Chapters 1 to 8) covers topics of classical phenotypic data analysis for prediction of breeding values in animal and plant breeding programs. In the second section (Chapters 9 to 13) we provide the concept and overall review of available tools for using DNA markers for predictions of genetic merits in breeding populations. With advances in DNA sequencing technologies, genomic data, especially single nucleotide polymorphism (SNP) markers, have become available for animal and plant breeding programs in recent years. Analysis of DNA markers for prediction of genetic merit is a relatively new and active research area. The algorithms and software to implement these algorithms are changing rapidly. This section represents state-of-the-art knowledge on the tools and technologies available for genetic analysis of plants and animals. However, readers should be aware that the methods or statistical packages covered here may not be available or they might be out of date in a few years. Ultimately the book is intended for professional breeders interested in utilizing these tools and approaches in their breeding programs. Lastly, we anticipate the usage of this volume for advanced level graduate courses in agricultural and breeding courses. |
| data analysis software for quantitative research: Quantitative Analysis Christopher P Halter, 2020-01-14 This introduction to quantitative analysis is designed is to assist the novice social science and educational researcher in interpreting statistical output data using the JASP open-source statistical analysis software. Through the examples and guidance, you will be able to select the statistical test that is appropriate for your data, apply the inferential test to your data, and interpret a statistical test's output table. These analysis methods include Contingency Tables, t-Tests, ANOVA, ANCOVA, Correlation, Linear Regression, Binomial tests, and Binomial Logistic Regression. The guide also includes procedures for Reliability and Exploratory Factor Analysis (EFA). The JASP application supports both Frequentist and Bayesian procedures. This guide is an update from Exploring Statistical Analysis (2018). |
| data analysis software for quantitative research: Data Analysis for Business, Economics, and Policy Gábor Békés, Gábor Kézdi, 2021-05-06 A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data. |
| data analysis software for quantitative research: Practical Statistics David Kremelberg, 2010-03-18 Making statistics—and statistical software—accessible and rewarding This book provides readers with step-by-step guidance on running a wide variety of statistical analyses in IBM® SPSS® Statistics, Stata, and other programs. Author David Kremelberg begins his user-friendly text by covering charts and graphs through regression, time-series analysis, and factor analysis. He provides a background of the method, then explains how to run these tests in IBM SPSS and Stata. He then progresses to more advanced kinds of statistics such as HLM and SEM, where he describes the tests and explains how to run these tests in their appropriate software including HLM and AMOS. This is an invaluable guide for upper-level undergraduate and graduate students across the social and behavioral sciences who need assistance in understanding the various statistical packages. |
| data analysis software for quantitative research: 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. |
| data analysis software for quantitative research: Computational Statistics Handbook with MATLAB Wendy L. Martinez, Angel R. Martinez, 2007-12-20 As with the bestselling first edition, Computational Statistics Handbook with MATLAB, Second Edition covers some of the most commonly used contemporary techniques in computational statistics. With a strong, practical focus on implementing the methods, the authors include algorithmic descriptions of the procedures as well as |
| data analysis software for quantitative research: Applied Missing Data Analysis Craig K. Enders, 2010-04-23 Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and models for handling missing not at random (MNAR) data. Easy-to-follow examples and small simulated data sets illustrate the techniques and clarify the underlying principles. The companion website includes data files and syntax for the examples in the book as well as up-to-date information on software. The book is accessible to substantive researchers while providing a level of detail that will satisfy quantitative specialists. This book will appeal to researchers and graduate students in psychology, education, management, family studies, public health, sociology, and political science. It will also serve as a supplemental text for doctoral-level courses or seminars in advanced quantitative methods, survey analysis, longitudinal data analysis, and multilevel modeling, and as a primary text for doctoral-level courses or seminars in missing data. |
| data analysis software for quantitative research: 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. |
| data analysis software for quantitative research: Qualitative Data Analysis Ian Dey, 2003-09-02 Qualitative Data Analysis shows that learning how to analyse qualitative data by computer can be fun. Written in a stimulating style, with examples drawn mainly from every day life and contemporary humour, it should appeal to a wide audience. |
| data analysis software for quantitative research: Data Analytics for the Social Sciences G. David Garson, 2021-11-30 Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science. It features applications in the R language, arguably the fastest growing and leading statistical tool for researchers. The book starts with an ethics chapter on the uses and potential abuses of data analytics. Chapters 2 and 3 show how to implement a broad range of statistical procedures in R. Chapters 4 and 5 deal with regression and classification trees and with random forests. Chapter 6 deals with machine learning models and the caret package, which makes available to the researcher hundreds of models. Chapter 7 deals with neural network analysis, and Chapter 8 deals with network analysis and visualization of network data. A final chapter treats text analysis, including web scraping, comparative word frequency tables, word clouds, word maps, sentiment analysis, topic analysis, and more. All empirical chapters have two Quick Start exercises designed to allow quick immersion in chapter topics, followed by In Depth coverage. Data are available for all examples and runnable R code is provided in a Command Summary. An appendix provides an extended tutorial on R and RStudio. Almost 30 online supplements provide information for the complete book, books within the book on a variety of topics, such as agent-based modeling. Rather than focusing on equations, derivations, and proofs, this book emphasizes hands-on obtaining of output for various social science models and how to interpret the output. It is suitable for all advanced level undergraduate and graduate students learning statistical data analysis. |
| data analysis software for quantitative research: Introduction to Spatial Econometrics James LeSage, Robert Kelley Pace, 2009-01-20 Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observat |
| data analysis software for quantitative research: Nonparametric Statistics with Applications to Science and Engineering Paul H. Kvam, Brani Vidakovic, 2007-08-24 A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods. |
| data analysis software for quantitative research: Development Research in Practice Kristoffer Bjärkefur, Luíza Cardoso de Andrade, Benjamin Daniels, Maria Ruth Jones, 2021-07-16 Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically. “In the DIME Analytics Data Handbook, the DIME team has produced an extraordinary public good: a detailed, comprehensive, yet easy-to-read manual for how to manage a data-oriented research project from beginning to end. It offers everything from big-picture guidance on the determinants of high-quality empirical research, to specific practical guidance on how to implement specific workflows—and includes computer code! I think it will prove durably useful to a broad range of researchers in international development and beyond, and I learned new practices that I plan on adopting in my own research group.†? —Marshall Burke, Associate Professor, Department of Earth System Science, and Deputy Director, Center on Food Security and the Environment, Stanford University “Data are the essential ingredient in any research or evaluation project, yet there has been too little attention to standardized practices to ensure high-quality data collection, handling, documentation, and exchange. Development Research in Practice: The DIME Analytics Data Handbook seeks to fill that gap with practical guidance and tools, grounded in ethics and efficiency, for data management at every stage in a research project. This excellent resource sets a new standard for the field and is an essential reference for all empirical researchers.†? —Ruth E. Levine, PhD, CEO, IDinsight “Development Research in Practice: The DIME Analytics Data Handbook is an important resource and a must-read for all development economists, empirical social scientists, and public policy analysts. Based on decades of pioneering work at the World Bank on data collection, measurement, and analysis, the handbook provides valuable tools to allow research teams to more efficiently and transparently manage their work flows—yielding more credible analytical conclusions as a result.†? —Edward Miguel, Oxfam Professor in Environmental and Resource Economics and Faculty Director of the Center for Effective Global Action, University of California, Berkeley “The DIME Analytics Data Handbook is a must-read for any data-driven researcher looking to create credible research outcomes and policy advice. By meticulously describing detailed steps, from project planning via ethical and responsible code and data practices to the publication of research papers and associated replication packages, the DIME handbook makes the complexities of transparent and credible research easier.†? —Lars Vilhuber, Data Editor, American Economic Association, and Executive Director, Labor Dynamics Institute, Cornell University |
| data analysis software for quantitative research: 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. |
| data analysis software for quantitative research: Introduction to Educational Research W. Newton Suter, 2012 W. Newton Suter argues that what is important in a changing education landscape is the ability to think clearly about research methods, reason through complex problems and evaluate published research. He explains how to evaluate data and establish its relevance. |
| data analysis software for quantitative research: MATLAB Guide Desmond J. Higham, Nicholas J. Higham, 2016-12-27 MATLAB is an interactive system for numerical computation that is widely used for teaching and research in industry and academia. It provides a modern programming language and problem solving environment, with powerful data structures, customizable graphics, and easy-to-use editing and debugging tools. This third edition of MATLAB Guide completely revises and updates the best-selling second edition and is more than 30 percent longer. The book remains a lively, concise introduction to the most popular and important features of MATLAB and the Symbolic Math Toolbox. Key features are a tutorial in Chapter 1 that gives a hands-on overview of MATLAB; a thorough treatment of MATLAB mathematics, including the linear algebra and numerical analysis functions and the differential equation solvers; and a web page at http://www.siam.org/books/ot150 that provides example program files, updates, and links to MATLAB resources. The new edition contains color figures throughout; includes pithy discussions of related topics in new ?Asides boxes that augment the text; has new chapters on the Parallel Computing Toolbox, object-oriented programming, graphs, and large data sets; covers important new MATLAB data types such as categorical arrays, string arrays, tall arrays, tables, and timetables; contains more on MATLAB workflow, including the Live Editor and unit tests; and fully reflects major updates to the MATLAB graphics system. This book is suitable for both beginners and more experienced users, including students, researchers, and practitioners. |
| data analysis software for quantitative research: Applied Thematic Analysis Greg Guest, Kathleen M. MacQueen, Emily E. Namey, 2012 This book provides step-by-step instructions on how to analyze text generated from in-depth interviews and focus groups, relating predominantly to applied qualitative studies. The book covers all aspects of the qualitative data analysis process, employing a phenomenological approach which has a primary aim of describing the experiences and perceptions of research participants. Similar to Grounded Theory, the authors' approach is inductive, content-driven, and searches for themes within textual data. |
| data analysis software for quantitative research: Research Design & Statistical Analysis Arnold D. Well, Jerome L. Myers, 2003-01-30 Free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats--Cover |
| data analysis software for quantitative research: An Introduction to Secondary Data Analysis with IBM SPSS Statistics John MacInnes, 2016-12-05 Many professional, high-quality surveys collect data on people′s behaviour, experiences, lifestyles and attitudes. The data they produce is more accessible than ever before. This book provides students with a comprehensive introduction to using this data, as well as transactional data and big data sources, in their own research projects. Here you will find all you need to know about locating, accessing, preparing and analysing secondary data, along with step-by-step instructions for using IBM SPSS Statistics. You will learn how to: Create a robust research question and design that suits secondary analysis Locate, access and explore data online Understand data documentation Check and ′clean′ secondary data Manage and analyse your data to produce meaningful results Replicate analyses of data in published articles and books Using case studies and video animations to illustrate each step of your research, this book provides you with the quantitative analysis skills you′ll need to pass your course, complete your research project and compete in the job market. Exercises throughout the book and on the book′s companion website give you an opportunity to practice, check your understanding and work hands on with real data as you′re learning. |
| data analysis software for quantitative research: Using Software in Qualitative Research Christina Silver, Ann Lewins, 2014-05-01 Using Software in Qualitative Research is an essential introduction to the practice and principles of Computer Assisted Qualitative Data Analysis (CAQDAS). The book will help you to choose the most appropriate package for your needs and get the most out of the software once you are using it. This book considers a wide range of tasks and processes in the data management and analysis process, and shows how software can help you at each stage. In the new edition, the authors present three case studies with different forms of data (text, video and mixed data) and show how each step in the analysis process for each project could be supported by software. The new edition is accompanied by an extensive companion website with step-by-step instructions produced by the software developers themselves. Software programmes covered in second edition include the latest versions of: ATLAS.ti DEDOOSE HyperRESEARCH MAXQDA NVivo QDA Miner TRANSANA Ann Lewins and Christina Silver are leading experts in the field of CAQDAS and have trained thousands of students and researchers in using software. Reading this book is like having Ann and Christina at your shoulder as you analyse your data! |
| data analysis software for quantitative research: SPSS Survival Manual Julie Pallant, 2007-08-01 Praise for previous editions: This book really is a life saver ... If the mere thought of statistics gives you a headache, then this is the book for you. - Statistics student, UK I just wanted to say how much I value Julie Pallant's SPSS Survival Manual. It’s quite the best text in SPSS I’ve encountered and I recommend it to anyone who’s listening! - Professor Carolyn Hicks, Birmingham University, UK ... one of the most useful functional pieces of instruction I have seen. So, gold star and thanks. - Instructional designer, USA There are several SPSS manuals published and this one really does 'do what it says on the tin' ... Whether you are a beginner doing your BSc or struggling with your PhD research (or beyond!), I wholeheartedly recommend this book. - British Journal of Occupational Therapy, UK Praise for the new edition: An excellent introduction to using SPSS for data analysis ... It provides a self-contained resource itself, with more than simply (detailed and clear) step-by-step descriptions of statistical procedures in SPSS. There is also a wealth of tips and advice, and for each statistical technique a brief, but consistently reliable, explanation is provided. - Associate Professor George Dunbar, Department of Psychology, University of Warwick, UK In this fully revised edition of her bestselling text, Julie Pallant guides you through the entire research process, helping you choose the right data analysis technique for your project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques. She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting SPSS output and an example of how to present the results in a report. For both beginners and experienced SPSS users in psychology, sociology, health sciences, medicine, education, business and related disciplines, the SPSS Survival Manual is an essential guide. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing. In this third edition all chapters have been updated to accommodate changes to SPSS procedures, screens and output in version 15. A new flowchart is included for SPSS procedures, and factor analysis procedures have been streamlined. It also includes more examples and material on syntax. Additional data files are available on the book's supporting website. |
Introduction to R for Data Analysis - UNC Greensboro
“R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes • an effective data handling and storage facility, • a suite of operators for …
INTRODUCTION TO SPSS FOR STATISTICAL ANALYSIS
• Descriptive statistics provide a summary of your data • Purpose of looking at descriptive statistics: (1) Check whether valid data are loaded properly E.g., unexpected values (e.g., 999, …
TOOLS AND BEST PRACTICES IN QUANTITATIVE RESEARCH
Sep 8, 2017 · from text to quantitative data Consilience: a tool that enables you to quickly read, understand, categorize, and derive insights from large quantities of unstructured text.
Statistical Treatment of data for Quantitative Research
Quantitative research relies heavily on the effective statistical treatment of data to extract meaningful insights and inform decision-making. This abstract outlines a comprehensive …
Quantitative Data Analysis: Choosing Between SPSS, PLS and …
With that in mind, the objective of this paper is twofold, namely to discuss the common statistical analysis and software used in social sciences studies and to suggest the right statistical...
Developing a Quantitative Data Analysis Plan - National …
Nov 25, 2013 · There are four main components of a DAP: background; aims; methods; and planned (dummy) tables and figures. Each research group may have different expectations of …
A Really Simple Guide to Quantitative Data Analysis
For primary data research: establish and conceptual framework and use it to design a data collection instrument to collect your primary data. For secondary data research: identify a data …
SPSS: An Imperative Quantitative Data Analysis Tool for
SPSS is a powerful and user-friendly software package for all sorts of statistical analysis of data (Levesque, 2007). This program is mostly used by students and researchers from the fields...
INTRODUCTION TO IBM SPSS STATISTICS AND THE DATA SET
There are a variety of software packages that do quantitative data analysis. R, SAS and Stata are all general purpose statistical analysis software packages. Excel and other spreadsheet …
Quantitative Data Analysis - Springer
book provides hands-on guidelines on (1) when to use which data analysis method, (2) what kind of data and data structure are required for each of the methods, (3) what each method does …
Introduction to SAS for Data Analysis - UNC Greensboro
SAS is an integrated software suite for advanced analytics, business intelligence, data management, and predictive analytics. You can use SAS software through both a graphical …
The Importance of Statistical Tools in Research Work - ARC …
Researchers use a wide range of statistical methods to analyze survey data. They do this using statistical software packages that are designed for research professionals. Popular programs …
Selection of Statistical Software for Solving Big Data Problems
Jan 29, 2019 · This article will examine four data analysis software—Excel add-ins, SPSS, SAS, and R—and we will outline the cost, training, and statistical methods/tests/uses for each of …
SPSS as a means for Scientific Analysis in Social Science …
SPSS is a computer programming software developed for the quantitative analysis in the social science research. It has different tools for the statistical analysis. It is really useful for the …
Creating a Data Analysis Plan: What to Consider When …
The purpose of this article is to help you create a data analysis plan for a quantitative study.
UNIT 19 COMPUTER DATA ANALYSIS - eGyanKosh
In this unit, we will introduce you to the software for quantitative and qualitative data analysis. We will provide in this details of SPSS package which is comparatively
The Contribution of Computer Software to Integrating …
In asking how does (or might) the use of computer software and processing power facilitate or extend integration of analyses, the key question for this paper relates to this issue of data...
Data Analysis Techniques for Quantitative Study - Springer
Quantitative methods focus on statistical, mathematical, or numerical analysis of data gathered or collected through questionnaires, surveys, or observational studies using computational …
UNIT 4 DATA ANALYSIS AND PRESENTATION Data Collection …
In the last, we have discussed software that are helpful in analysing data for both qualitative and quantitative research. Before proceeding to study the unit, look at the objectives of studying …
Introduction to R for Data Analysis - UNC Greensboro
“R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes • an effective data handling and storage facility, • a suite of operators for …
INTRODUCTION TO SPSS FOR STATISTICAL ANALYSIS
• Descriptive statistics provide a summary of your data • Purpose of looking at descriptive statistics: (1) Check whether valid data are loaded properly E.g., unexpected values (e.g., 999, …
Use of Software Packages for Analysis: Quantitative Analysis …
6. Types of Software Packages for Quantitative Research Researchers generally use five main software packages for quantitative research. A brief description of each follows. Statistical …
TOOLS AND BEST PRACTICES IN QUANTITATIVE …
Sep 8, 2017 · from text to quantitative data Consilience: a tool that enables you to quickly read, understand, categorize, and derive insights from large quantities of unstructured text.
Statistical Treatment of data for Quantitative Research
Quantitative research relies heavily on the effective statistical treatment of data to extract meaningful insights and inform decision-making. This abstract outlines a comprehensive …
Quantitative Data Analysis: Choosing Between SPSS, PLS …
With that in mind, the objective of this paper is twofold, namely to discuss the common statistical analysis and software used in social sciences studies and to suggest the right statistical...
Developing a Quantitative Data Analysis Plan - National …
Nov 25, 2013 · There are four main components of a DAP: background; aims; methods; and planned (dummy) tables and figures. Each research group may have different expectations of …
A Really Simple Guide to Quantitative Data Analysis
For primary data research: establish and conceptual framework and use it to design a data collection instrument to collect your primary data. For secondary data research: identify a data …
SPSS: An Imperative Quantitative Data Analysis Tool for
SPSS is a powerful and user-friendly software package for all sorts of statistical analysis of data (Levesque, 2007). This program is mostly used by students and researchers from the fields...
INTRODUCTION TO IBM SPSS STATISTICS AND THE …
There are a variety of software packages that do quantitative data analysis. R, SAS and Stata are all general purpose statistical analysis software packages. Excel and other spreadsheet …
Quantitative Data Analysis - Springer
book provides hands-on guidelines on (1) when to use which data analysis method, (2) what kind of data and data structure are required for each of the methods, (3) what each method does …
Introduction to SAS for Data Analysis - UNC Greensboro
SAS is an integrated software suite for advanced analytics, business intelligence, data management, and predictive analytics. You can use SAS software through both a graphical …
The Importance of Statistical Tools in Research Work - ARC …
Researchers use a wide range of statistical methods to analyze survey data. They do this using statistical software packages that are designed for research professionals. Popular programs …
Selection of Statistical Software for Solving Big Data Problems
Jan 29, 2019 · This article will examine four data analysis software—Excel add-ins, SPSS, SAS, and R—and we will outline the cost, training, and statistical methods/tests/uses for each of …
SPSS as a means for Scientific Analysis in Social Science …
SPSS is a computer programming software developed for the quantitative analysis in the social science research. It has different tools for the statistical analysis. It is really useful for the …
Creating a Data Analysis Plan: What to Consider When …
The purpose of this article is to help you create a data analysis plan for a quantitative study.
UNIT 19 COMPUTER DATA ANALYSIS - eGyanKosh
In this unit, we will introduce you to the software for quantitative and qualitative data analysis. We will provide in this details of SPSS package which is comparatively
The Contribution of Computer Software to Integrating …
In asking how does (or might) the use of computer software and processing power facilitate or extend integration of analyses, the key question for this paper relates to this issue of data...
Data Analysis Techniques for Quantitative Study - Springer
Quantitative methods focus on statistical, mathematical, or numerical analysis of data gathered or collected through questionnaires, surveys, or observational studies using computational …
UNIT 4 DATA ANALYSIS AND PRESENTATION Data …
In the last, we have discussed software that are helpful in analysing data for both qualitative and quantitative research. Before proceeding to study the unit, look at the objectives of studying …
