In covering both traditional and newer approaches, and presenting them alongside each other, and by consistently referring to two data sets throughout, this book provides students with a brand-new way of understanding methods and a tool with which they can think about their own research.
In covering both traditional and newer approaches, and presenting them alongside each other, and by consistently referring to two data sets throughout, this book provides students with a brand-new way of understanding methods and a tool with which they can think about their own research.
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.
Inhaltsangabe
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
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
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
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
Rezensionen
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'.
Benoît Rihoux
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