Handbook of Data Analysis
Sold by Better World Books Ltd, Dunfermline, United Kingdom
AbeBooks Seller since 13 October 2008
Used - Hardcover
Condition: Used - Good
Ships from United Kingdom to U.S.A.
Quantity: 2 available
Add to basketSold by Better World Books Ltd, Dunfermline, United Kingdom
AbeBooks Seller since 13 October 2008
Condition: Used - Good
Quantity: 2 available
Add to basketFormer library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Seller Inventory # GRP9707747
This is a book that will rapidly be recognized as the bible for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. However, the book also seeks to enhance debate in the field by tackling more advanced topics such as models of change, causality, panel models and network analysis. Specialists will find much food for thought in these chapters.
A distinctive feature of the book is the breadth of coverage. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.
`The book provides researchers with guidance in, and examples of, both quantitative and qualitative modes of analysis, written by leading practitioners in the field. The editors give a persuasive account of the commonalities of purpose that exist across both modes, as well as demonstrating a keen awareness of the different things that each offers the practising researcher′ - Clive Seale, Brunel University
`With the appearance of this handbook, data analysts no longer have to consult dozens of disparate publications to carry out their work. The essential tools for an intelligent telling of the data story are offered here, in thirty chapters written by recognized experts. While quantitative methods are treated, from basic statistics through the general linear model and beyond, qualitative methods are by no means neglected. Indeed, a unique feature of this volume is the careful integration of quantitative and qualitative approaches. Undoubtedly, this integration succeeds because of the research strengths of the editors, leading social researchers who themselves employ both quantitative and qualitative methods′ - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa and Editor of the SAGE `Quantitative Applications in the Social Sciences′ series
`This is an excellent guide to current issues in the analysis of social science data. I recommend it to anyone who is looking for authoritative introductions to the state of the art. Each chapter offers a comprehensive review and an extensive bibliography and will be invaluable to researchers wanting to update themselves about modern developments′ - Professor Nigel Gilbert, Pro Vice-Chancellor and Professor of Sociology, University of Surrey
Melissa Hardy is a Distinguished Professor Emeritus of Sociology and Demography at Penn State University in University Park. She is an alumna of Albright College and Indiana University in Bloomington. Her research focused on aging and the life course, retirement and age-stratified transitions, self-assessed health, and political attitudes using longitudinal data and a range of quantitative techniques. Her published work appears in American Sociological Review, Social Forces, Journal of Health and Social Behavior, and Demography. She enjoyed teaching social statistics and general linear models to graduate and undergraduates students, using everyday experiences to help them understand the meaning of statistical concepts.
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