Analysing Quantitative Data
Welcome to the companion website for Raymond Kent’s Analysing Quantitative Data. Variable-based and Case-based Approaches to Non-experimental Data (Sage Publications, 2015). On this website, you will find, for both students and lecturers, on a chapter by chapter basis:
- A chapter summary
- Recommended reading
- Links to SAGE journal articles
- Answers to exercises from the book
- PowerPoint slides
In addition, there is:
- An overview of data analysis packages
- An introduction to SPSS
- Weblinks to alternative datasets
The 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 students to learn a range of approaches and to understand which may be the most appropriate for their research. In particular, a case-based configurational approach to datasets using elements of fuzzy logic offers a way of analysing datasets very different from the more usual statistical procedures.
Using multidisciplinary non-experimental datasets, the book demonstrates that data analysis is really an active dialogue between ideas and evidence, between research objectives and data in a dataset. One particular dataset is returned to throughout the chapters, enabling readers to see the role of the researcher in action; it also showcases the differences between each approach and the significance of the different decisions that must be made as researchers move through their analyses.
The book is divided into four clear sections:
- The nature of data, datasets and their preparation
- Variable-based analyses
- Case-based analyses
- Comparing approaches and communicating the results
Clear, original and written for students, this book should be compulsory reading for anyone looking to analyse data derived from non-experimental research settings, that is, data generated largely from various kinds of survey, but which may also be a result of using electronic or observational data capture techniques. This book should be of interest to final-year undergraduates and postgraduates who are undertaking modules or courses in research methodology in the areas of sociology, business studies, marketing, health and education. In particular, it should be of interest to students who are doing projects, dissertations or theses and who are wondering what approaches to data analysis are possible and what data analysis strategies they should adopt. It should also be of interest to researchers who usually go to great lengths to construct their data, but often find that traditional, variable-based statistics produce disappointing or inconclusive results.
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