Analysing Quantitative Data

SAGE PUBLICATIONS LTDISBN: 9781446273401

Variable-based and Case-based Approaches to Non-experimental Datasets

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By Raymond A. Kent
Imprint: SAGE PUBLICATIONS LTD
Release Date:
Format: HARDBACK
Dimensions: 242 x 170 mm
Weight: 820 g
Pages: 376

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Description

This innovative book provides a fresh take on quantitative data analysis within the social sciences. It presents variable-based and case-based approaches side-by-side encouraging you to learn a range of approaches and to understand which is the most appropriate for your research. Using two multidisciplinary non-experimental datasets throughout, the book demonstrates that data analysis is really an active dialogue between ideas and evidence. Each dataset is returned to throughout the chapters enabling you to see the role of the researcher in action; it also showcases the difference between each approach and the significance of researchers' decisions that must be made as you move through your analysis. The book is divided into four clear sections: Data and their presentation Variable-based analyses Case-based analyses Comparing and combining approaches Clear, original and written for students this book should be compulsory reading for anyone looking to conduct non-experimental quantitative data analysis.

Ray Kent is now retired, but was Senior Lecturer in Marketing at the University of Stirling. He has published on topics as diverse as product range policy, marketing communications with sensitive groups, private trading on the internet, improving email responses and the use of fuzzy logic in data analysis. This is his eighth book; earlier books have been in the areas of the history of sociological research, survey data analysis and marketing research. After each book, he says it will be his last. We'll see.

Part 1: Quantitative data: structure, preparation and analysis approaches Chapter 1: Data structure Chapter 2: Data preparation Chapter 3: Approaches to data analysis Part 2: Variable-based analyses Chapter 4: Univariate analysis Chapter 5: Bivariate analysis Chapter 6: Multivariate analysis Part 3: Case-based analyses Chapter 7: Set-theoretic methods and configurational data analysis Chapter 8: Cluster and discriminant analysis Part 4: Comparing and communicating results Chapter 9: Comparing and mixing methods Chapter 10: Evaluating hypotheses, explaining and communicating results

This compelling textbook provides a clear view of a broad range of possibilities for quantitative data, complementing the statistical toolbox with configurational methods. A must read for students aiming to get more out of data and move beyond 'push-button analysis'. -- Benoit Rihoux

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