Analysing Quantitative Data: Variable-based and Case-based Approaches to Non-experimental Datasets
By: Raymond A. Kent (author)Paperback
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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 presentationVariable-based analysesCase-based analysesComparing 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 approachesChapter 1: Data structureChapter 2: Data preparationChapter 3: Approaches to data analysisPart 2: Variable-based analysesChapter 4: Univariate analysisChapter 5: Bivariate analysisChapter 6: Multivariate analysisPart 3: Case-based analysesChapter 7: Set-theoretic methods and configurational data analysisChapter 8: Cluster and discriminant analysisPart 4: Comparing and communicating resultsChapter 9: Comparing and mixing methodsChapter 10: Evaluating hypotheses, explaining and communicating results
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- ID: 9781446273418
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