Improving Surveys with Paradata: Analytic Uses of Process Information
Publication Date: 2013
Explore the practices and cutting-edge research on the new and exciting topic of paradata Paradata are measurements related to the process of collecting survey data. Improving Surveys with Paradata: Analytic Uses of Process Information is the most accessible and comprehensive contribution to this up-and-coming area in survey methodology. Featuring contributions from leading experts in the field, Improving Surveys with Paradata: Analytic Uses of Process Information introduces and reviews issues involved in the collection and analysis of paradata. The book presents readers with an overview of the indispensable techniques and new, innovative research on improving survey quality and total survey error. Along with several case studies, topics include: Using paradata to monitor fieldwork activity in face-to-face, telephone, and web surveys Guiding intervention decisions during data collection Analysis of measurement, nonresponse, and coverage error via paradata Providing a practical, encompassing guide to the subject of paradata, the book is aimed at both producers and users of survey data. Improving Surveys with Paradata: Analytic Uses of Process The book also serves as an excellent resource for courses on data collection, survey methodology, and nonresponse and measurement error.
Just Plain Data Analysis: Finding, Presenting, and Interpreting Social Science Data
Call Number: HA 29 .K58 2008
Publication Date: 2008
Just Plain Data Analysis is designed to teach students statistical literacy skills that they can use to evaluate and construct arguments about public affairs issues grounded in numerical evidence. Students will learn to find, interpret, and present commonly used social indicators, which are the quantitative measures of the performance of societies' institutions. Although critical for careful social science research, these skills are not often covered in qualitative or quantitative research methods and statistics texts. Clear, concise, and readable, Just Plain Data Analysis will support students' work in a variety of courses, stimulate critical thinking, and be a helpful reference in future careers. Book jacket.
International Handbook of Survey Methodology
Call Number: HA 31.2 .I565 2008
Publication Date: 2008
Taking into account both traditional and emerging modes, this comprehensive new Handbook covers all major methodological and statistical issues in designing and analyzing surveys. With contributions from the world's leading survey methodologists and statisticians, this invaluable new resource provides guidance on collecting survey data and creating meaningful results. Featuring examples from a variety of countries, the book reviews such things as how to deal with sample designs, write survey questions, and collect data on the Internet. A thorough review of the procedures associated with multiple modes of collecting sample survey information and applying that combination of methods that fit the situation best is included. The International Handbook of Survey Methodology opens with the foundations of survey design, ranging from sources of error, to ethical issues. This is followed by a section on design that reviews sampling challenges and tips on writing and testing questions for multiple methods. Part three focuses on data collection, from face-to-face interviews, to Internet and interactive voice response, to special challenges involved in mixing these modes within one survey. Analyzing data from both simple and complex surveys is then explored, as well as procedures for adjusting data. The book concludes with a discussion of maintaining quality. Intended for advanced students and researchers in the behavioral, social, and health sciences, this "must have" resource will appeal to those interested in conducting or using survey data from anywhere in the world, especially those interested in comparing results across countries. The book also serves as a state-of-the-art text for graduate level courses and seminars on survey methodology. A companion website contains additional readings and examples.
Analysis of Multivariate Social Science Data
Call Number: HA 29 .A5824 2008
Publication Date: 2008
Drawing on the authors' varied experiences working and teaching in the field, Analysis of Multivariate Social Science Data, Second Editionenables a basic understanding of how to use key multivariate methods in the social sciences. With updates in every chapter, this edition expands its topics to include regression analysis, confirmatory factor analysis, structural equation models, and multilevel models. After emphasizing the summarization of data in the first several chapters, the authors focus on regression analysis. This chapter provides a link between the two halves of the book, signaling the move from descriptive to inferential methods and from interdependence to dependence. The remainder of the text deals with model-based methods that primarily make inferences about processes that generate data. Relying heavily on numerical examples, the authors provide insight into the purpose and working of the methods as well as the interpretation of data. Many of the same examples are used throughout to illustrate connections between the methods. In most chapters, the authors present suggestions for further work that go beyond conventional exercises, encouraging readers to explore new ground in social science research. Requiring minimal mathematical and statistical knowledge, this book shows how various multivariate methods reveal different aspects of data and thus help answer substantive research questions.
The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives
Call Number: HB 137 .Z55 2008
Publication Date: 2008-02-18
McCloskey and Ziliak have been pushing this very elementary, very correct, very important argument through several articles over several years and for reasons I cannot fathom it is still resisted. If it takes a book to get it across, I hope this book will do it. It ought to.Thomas Schelling, Distinguished University Professor, School of Public Policy, University of Maryland, and 2005 Nobel Prize Laureate in Economics With humor, insight, piercing logic and a nod to history, Ziliak and McCloskey show how economists and other scientists suffer from a mass delusion about statistical analysis. The quest for statistical significance that pervades science today is a deeply flawed substitute for thoughtful analysis. . . . Yet few participants in the scientific bureaucracy have been willing to admit what Ziliak and McCloskey make clear: the emperor has no clothes. Kenneth Rothman, Professor of Epidemiology, Boston University School of Health The Cult of Statistical Significanceshows, field by field, how statistical significance, a technique that dominates many sciences, has been a huge mistake. The authors find that researchers in a broad spectrum of fields, from agronomy to zoology, employ testing that doesn't test and estimating; that doesn't estimate. The facts will startle the outside reader: how could a group of brilliant scientists wander so far from scientific magnitudes? This study will encourage scientists who want to know how to get the statistical sciences back on track and fulfill their quantitative promise. The book shows for the first time how wide the disaster is, and how bad for science, and it traces the problem to its historical, sociological, and philosophical roots. Stephen T. Ziliak is the author or editor of many articles and two books. He currently lives in Chicago, where he is Professor of Economics at Roosevelt University. Deirdre N. McCloskey, Distinguished Professor of Economics, History, English, and Communication at the University of Illinois at Chicago, is the author of twenty books and three hundred scholarly articles. She has held Guggenheim and National Humanities Fellowships. She is best known forHow to Be Human* Though an Economist(University of Michigan Press, 2000) and her most recent book,The Bourgeois Virtues: Ethics for an Age of Commerce(2006).
Discovering Statistics Using SPSS: (and Sex and Drugs and Rock 'n' Roll)
Call Number: HA 32 .F54 2009
Publication Date: 2009
Tony C. Brown examines "the inescapable yet infinitely troubling figure of the not-quite-nothing" in Enlightenment attempts to think about the aesthetic and the savage. The various texts Brown considers--including the writings of Addison, Rousseau, Kant, and Defoe--turn to exotic figures in order to delimit the aesthetic, and to aesthetics in order to comprehend the savage. In his intriguing exploration Brown discovers that the primitive introduces into the aesthetic and the savage an element that proves necessary yet difficult to conceive. At its most profound, Brown explains, this element engenders a loss of confidence in one's ability to understand the human's relation to itself and to the world. That loss of confidence--what Brown refers to as a breach in anthropological security--traces to an inability to maintain a sense of self in the face of the New World. Demonstrating the impact of the primitive on the aesthetic and the savage, he shows how the eighteenth-century writers he focuses on struggle to define the human's place in the world. As Brown explains, these authors go back again and again to "exotic" examples from the New World--such as Indian burial mounds and Maori tattooing practice--making them so ubiquitous that they come to underwrite, even produce, philosophy and aesthetics.
Social Statistics for a Diverse Society
Call Number: HA 29 .N25 2006
Publication Date: 2005
Written especially for undergraduate students taking their first course in social statistics, this highly accessible bestselling text has been thoroughly revised and updated with the latest General Social Survey data. This new Fourth Edition maintains the same informal, conversational writing style along with the many pedagogical features have led to the previous editions' widespread success. It also introduces new social issues, including more analysis of cultural diversity. In this Fourth Edition, the authors have introduced a strong global perspective by using real-life examples from the International Social Survey Programme that help expand the students' analytical focus beyond the United States.
Statistical Methods in e-Commerce Research
Call Number: HF 5548.32 .J368 2008
Publication Date: 2008
This groundbreaking book introduces the application of statistical methodologies to e-Commerce data With the expanding presence of technology in today's economic market, the use of the Internet for buying, selling, and investing is growing more popular and public in nature. Statistical Methods in e-Commerce Research is the first book of its kind to focus on the statistical models and methods that are essential in order to analyze information from electronic-commerce (e-Commerce) transactions, identify the challenges that arise with new e-Commerce data structures, and discover new knowledge about consumer activity. This collection gathers over thirty researchers and practitioners from the fields of statistics, computer science, information systems, and marketing to discuss the growing use of statistical methods in e-Commerce research. From privacy protection to economic impact, the book first identifies the many obstacles that are encountered while collecting, cleaning, exploring, and analyzing e-Commerce data. Solutions to these problems are then suggested using established and newly developed statistical and data mining methods. Finally, a look into the future of this evolving area of study is provided through an in-depth discussion of the emerging methods for conducting e-Commerce research. Statistical Methods in e-Commerce Research successfully bridges the gap between statistics and e-Commerce, introducing a statistical approach to solving challenges that arise in the context of online transactions, while also introducing a wide range of e-Commerce applications and problems where novel statistical methodology is warranted. It is an ideal text for courses on e-Commerce at the upper-undergraduate and graduate levels and also serves as a valuable reference for researchers and analysts across a wide array of subject areas, including economics, marketing, and information systems who would like to gain a deeper understanding of the use of statistics in their work.
Statistical Methods for Organizational Research: Theory and Practice
Call Number: HD 30.4 .D484 2004
Publication Date: 2004
This clearly written textbook clarifies the concepts underpinning descriptive and inferential statistics in organizational research. Acting as much more than a theoretical reference tool, step-by-step it guides readers through the various key stages of successful data analysis. Covering everything from introductory descriptive statistics to advanced inferential techniques such as ANOVA, multiple and logistic regression and factor analysis, this is one of the most comprehensive textbooks available. Using examples directly relevant to organizational research it includes practical advice on such topics as the size of samples required in research studies, using and interpreting SPSS, and writing up results. In helping readers to develop a sound understanding of statistical methods, rather than focusing on complex formulas and computations, this outstanding textbook is as appropriate for those who wish to refresh their knowledge as those new to the subject area.
Statistical Methods for Practice and Research: A Guide to Data Analysis Using SPSS
Call Number: HA 32 .G38 2009
Publication Date: 2009
This book is designed to help the managers and researchers in solving statistical problems using SPSS and to help them understand how they can use various statistical tools for their own research problems. SPSS is a very powerful and user friendly computer package for data analyses. It can take data from most other file-types and generate tables, charts, plots, and descriptive statistics, and conduct complex statistical analyses. This book will help students, business managers, academics as well as practicing researchers to solve statistical problems using the latest version of SPSS (16.0). After providing a brief overview of SPSS and basic statistical concepts, the book covers: Descriptive statistics t-tests, chi-square tests, and ANOVA Correlation analysis Multiple and logistics regression Factor analysis and testing scale reliability Advanced data handling