Using Secondary Data in Educational and Social Research by
"The book is written in an admirably clear style and is effectively structured throughout its three parts with eight concise chapters. The book's intention - in which it largely succeeds - is to strengthen secondary data analysis as one technique in the 'methodological toolbox' available to researchers, one which has been on the margin for far too long." British Journal of Educational Technology Secondary data is a powerful tool for providing context to an otherwise small-scale study, as well as being an efficient way of bringing together a large amount of data, particularly where access to the field may be difficult. This comprehensive guide introduces students to the use of secondary data in educational and social research, and provides a practical resource for researchers who are new to the field of secondary data analysis. The author encourages researchers to consider the potential for using secondary data both as their primary research method, but also as a useful strategy in mixed methods designs. The first part of the book explores the role of secondary data analysis in contemporary social research. It considers the arguments for and against its use and addresses its particular benefits in mixed method research designs, especially those in the political arithmetic tradition. The second part introduces worked examples which show the potential for using secondary sources to answer a varied range of research questions. It provides step-by-step guidance on how to manipulate and analyse secondary data. The inclusion of recent national and international datasets as exemplars allows students to place their research in a 'real life' context and to consider current and topical research issues.
Interpreting Official Statistics by
Interpreting Official Statistics examines the official statistics produced about the current state of British society. It documents some of the ways in which information has been suppressed, manipulated and misinterpreted since 1979. This invaluable guide is designed to help students know what figures are available, and to discover when and how politicians are misusing statistics. Data sets covered include: * Households below average income * Administrative and survey methods of unemployment and crime * Population census data on ethnicity * Data sources on women and work * Data on the relationship between class and health, and safety at work * New data sources on disability * Labour Force Survey.
Statistical Modelling for Social Researchers by
This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist looking to apply statistical modelling techniques in research. The book also serves as an introduction for those wishing to develop more detailed knowledge and skills in statistical modelling. Rather than present a limited number of statistical models in great depth, the aim is to provide a comprehensive overview of the statistical models currently adopted in social research, in order that the researcher can make appropriate choices and select the most suitable model for the research question to be addressed. To facilitate application, the book also offers practical guidance and instruction in fitting models using SPSS and Stata, the most popular statistical computer software which is available to most social researchers. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic regression, log-linear models, multilevel models, latent variable models (factor analysis), path analysis and simultaneous equation models and models for longitudinal data and event histories. An accompanying website hosts the datasets and further exercises in order that the reader may practice developing statistical models. An ideal tool for postgraduate social science students, research students and practicing social researchers in universities, market research, government social research and the voluntary sector.
Analyzing Quantitative Data by
What basic knowledge and skills do novice researchers in social science require? How can students be helped to over-come 'symbol phobia' or 'figure blindness'? This generous and constantly insightful book is designed for social researchers who need to know what procedures to use under what circumstances, in practical research projects. It accomplishes this without requiring an in-depth understanding of statistical theory, but also avoids both trivializing procedures or resorting to 'cookbook' techniques. Among the key features of the book are:- Accessibility- Organization of the wide, often bewildering array of methods of data analysis into a coherent and user-friendly scheme of classification: types of analysis and levels of measurement- Demystification - the first chapter unpacks commonly taken-for-granted concepts such as 'analysis', 'data' and 'quantitative'- Location of methods in real research problemsThe book is a triumphant introduction to the theory and practice of quantitative methods. It will quickly establish itself as essential reading for students doing social research throughout the social sciences.'With this book Norman Blaikie retains his reputation as the leading rapporteur and raconteur of social research methodology. With many other introductory texts, data analysis becomes just an exercise unto itself, and students (sometimes) learn to go through the motions without really knowing why. After working with Blaikie's text, novice researchers will know why quantitative inquiry is important' - Ray Pawson, University of Leeds
Research Methods and Statistics in Psychology by
The seventh edition of Research Methods and Statistics in Psychologyprovides students with the most readable and comprehensive survey of research methods, statistical concepts and procedures in psychology today. Assuming no prior knowledge, this bestselling text takes you through every stage of your research project giving advice on planning and conducting studies, analysing data and writing up reports. The book provides clear coverage of experimental, interviewing and observational methods, psychological testing, qualitative methods and analysis and statistical procedures which include nominal level tests, multi-factorial ANOVA designs, multiple regression, log linear analysis, and factor analysis.　It features detailed and illustrated SPSS instructions for all these and other procedures, eliminating the need for an extra SPSS textbook. New features to this edition include: Additional coverage of factor analysis and online and modern research methods Expanded coverage of report writing guidelines References updated throughout Presentation updated throughout, to include more figures, tables and full colour to help break up the text Companion website signposted throughout the book to improve student usability Improved and extended web links and further reading associated with every chapter. Each chapter contains a glossary, key terms and newly integrated exercises, ensuring that key concepts are understood. A fully updated companion website (www.routledge.com/cw/coolican) provides additional exercises, testbanks for each chapter, revision flash cards, links to further reading and data for use with SPSS.
Analyzing Social Science Data by
In this novel and refreshing textbook, David de Vaus directs students to the core of data analysis. The book is an authoritative guide to the problems facing beginners in the field. Analyzing Social Science Data guides students in: problems with the initial data; problems with the initial variables; how to handle too much data; how to generalize; problems of analyzing single variables; problems examining bivariate relationships; and problems examining multivariate relationships The book is a tour de force in making data analysis manageable and rewarding for today's undergraduate studying research methods.'I'm full of admiration for this book. Once again, David de Vaus has come up with a superb book that is well written and organized and which will be a boon to a wide range of students. He has taken a vast array of problems that users of quantitative data analysis procedures are likely to encounter. The selection of issues and problems ... reflects the experience of a true practitioner with a grasp of his field and of the intricacies of the research process. The selection of issues clearly derives also from experience of teaching students how to do research and analyse data....A large number of practitioners will want the book. I was surprised at how much I learned from this. This will be a vital book for the bookshelves of practitioners of the craft of quantitative data analysis' - Alan Bryman, Professor of Social Research, Loughborough University
Understanding Social Statistics by
This fully revised, expanded and updated Second Edition of the bestselling textbook by Jane Fielding and Nigel Gilbert provides a comprehensive yet accessible guide to quantitative data analysis. Designed to help take the fear out of the use of numbers in social research, this textbook introduces students to statistics as a powerful means of revealing patterns in human behavior. The textbook covers everything typically included in an introductory course on social statistics for students in the social sciences and the authors have taken the opportunity of this Second Edition to bring the data sources as current as possible. The book is full of up-to-date examples and useful and clear illustrations using the latest SPSS software. While maintaining the student-friendly elements of the first, such as chapter summaries, exercises at the end of each chapter, and a glossary of key terms, new features to this edition include:Updated examples and references SPSS coverage and screen-shots now incorporate the current version 14.0 and are used to demonstrate the latest social statistics datasetsAdditions to content include a brand new section on developing a coding frame and an additional discussion of weighting counts as a means of analyzing published statisticsEnhanced design aids navigation which is further simplified by the addition of core objectives for each chapter and bullet-pointed chapter summariesThe updated Website at http:/www.soc.surrey.ac.uk/uss/index.html reflects changes made to the text and provides updated datasetsA valuable and practical guide for students dealing with the large amounts of data that are typically collected in social surveys, the Second Edition of Understanding Social Statistics is an essential textbook for courses on statistics and quantitative research across the social sciences.
Understanding and Using Advanced Statistics by
Understanding and Using Advanced Statistics is a comprehensive, practical guide for postgraduate students advising how and when to use more advanced statistical methods. Perfect for students without a mathematical background, the authors refresh important basics such as descriptive statistics and research design as well as introducing essential upper-level techniques to cater for the advanced student. Key Features: - Comprehensive guide informing how to use a range of advanced statistical methods such as MANOVA, path analysis and logistical regression; - Inter-disciplinary: ideal for students studying upper level statistical methods in any subject across the social sciences; - Practical guide: case studies, further reading, key terms explained in order to help the non-mathematically orientated student get ahead with their research. Building on undergraduate statistical grounding, Understanding and Using Advanced Statistics provides the upper-level researcher with the knowledge of what advanced statistics do, how they should be used, and what their output means.
Data Construction and Data Analysis for Survey Research by
Based on the needs of business, marketing and social science students, this book provides an accessible and easy-to-follow guide to survey data analysis. The book avoids the more usual statistics-driven perspective. Rather, it provides an intuitive feel for handling survey data by emphasising that data analysis is more about understanding the research objectives, what kinds of data have been collected, how quantitative data were generated by the process of measurement, how to create a data matrix and how to transform raw data before thinking about appropriate statistical calculations. The author begins by considering what data are, the different kinds of data that surveys generate, and the tripartite format of all quantitative data. The processes of measurement and the errors that may arise are carefully explained. Coverage of the creation and analysis of a data matrix using SPSS is then provided. The author then reviews what kinds of statistical procedure are required for what kinds of data and for what purposes. The book concludes by giving a review of strategies for coping with all the kinds of practical problems that arise in survey research. Reader-friendly throughout, Data Analysis: A Guide to Market and Social Research provides numerous worked examples, end-of-chapter questions and points for further discussion to help reinforce concepts learnt. A data diskette containing the worked examples in SPSS is also provided in the back of the book. Also available is a companion website with extra features to accompany the text, please take a look by clicking below - http://www.palgrave.com/business/kent/index.asp
Surveys in Social Research by
David de Vaus' classic text Surveys in Social Researchprovides clear advice on how to plan, conduct and analyse social surveys. It emphasises the links between theory and research, the logic and interpretation of statistics and the practices of social research. This sixth edition has been completely revised and updated, and contains new examples, data and extensive lists of web resources. As well as explaining how to conduct good surveys, de Vaus shows how to become a critical consumer of research. He argues that the logic of surveys and statistics is simply an extension of the logic we use in everyday life; analysis, however, requires creativity and imagination rather than the application of sterile mechanical procedures. The prime goal of research should be to gain accurate understanding and, as a researcher, use methods and techniques which enhance understanding. De Vaus advocates researchers use the method, rather than letting the method use you. Surveys in Social Researchis essential reading for students and researchers working with surveys. It assumes no background in statistical analysis, and gives you the tools you need to come to grips with this often challenging field of work.
An Introduction to Secondary Data Analysis with IBM SPSS Statistics by
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.
Multivariate Statistical Methods by
Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.
Exploring Data by
The updated edition of this classic text introduces a range of techniques for exploring quantitative data. Beginning with an emphasis on descriptive statistics and graphical approaches, it moves on in later chapters to simple strategies for examining the associations between variables using inferential statistics such as chi squared. The book has been substantially revised to include the most recent approaches to data analysis, and includes step-by-step instructions on using SPSS. All these techniques are illustrated with intriguing real examples, drawn from important social research over the past three decades, designed to illuminate significant sociological and political debates. The book shows how students can use quantitative data to answer various questions: Is it true that the rich are getting richer and the poor are getting poorer? Are crime rates really going down, and how can we tell? How much alcohol do men and women really drink in an average week? Which country in Europe has the highest average working hours? Readers are encouraged to explore data for themselves, and are carefully guided through the opportunities and pitfalls of using statistical packages, as well as the numerous data sources readily available online. Suitable for those with no previous experience of quantitative data analysis, the second edition of Exploring Data will be invaluable to students across the social sciences. Download answers to exercises in book.