Interpreting Quantitative Data

About the Book

How do quantitative methods help us to acquire knowledge of the real world? What are the `do′s′ and `don′ts′ of effective quantitative research?

This refreshing and accessible book provides students with a novel and useful resource for doing quantitative research. It offers students a guide on how to: interpret the complex reality of the social world; achieve effective measurement; understand the use of official statistics; use social surveys; understand probability and quantitative reasoning; interpret measurements; apply linear modelling; understand simulation and neural nets; and integrate quantitative and qualitative modelling in the research process.

Jargon-free and written with the needs of students in mind, the book will be required reading for students interested in using quantitative research methods.

Table of Contents:
Introduction Interpreting the Real and Describing the Complex Why We Have to Measure The Nature of Measurement What We Measure and How We Measure The State′s Measurement The Construction and Use of Official Statistics Measuring the Complex World The Character of Social Surveys Probability and Quantitative Reasoning Interpreting Measurements Exploring, Describing and Classifying Linear Modelling Clues as to Causes Coping with Non-Linearity and Emergence Simulation and Neural Nets Qualitative Modelling Issues of Meaning and Cause Conclusion

About the Author :
David Byrne is Emeritus Professor of Sociology and Applied Social Sciences at the University of Durham. He has published widely on the methodology of social research, for example, in Interpreting Quantitative Data (2002) and with Charles Ragin edited The SAGE Handbook of Case Based Methods (2009). His major theoretical engagement is with the deployment of the complexity frame of reference across the social sciences—see Complexity Theory and the Social Sciences: The State of the Art (with Gillian Callaghan, 2011) with a particular focus on application to policy and practice. His current research focus is on the implications of the transition to the post-industrial in welfare capitalism—Paying for the Welfare State in the 21st Century (with Sally Ruane, 2011) and Class After Industry (2018).

Review :
This is a good book on interpreting, rather than simply creating, statistics. It raises awareness of the difficulties in interpreting data when, for example, variables have been deleted or, at a more advanced level, structural equation modeling has been used. A very useful reference work for people who need to work with statistics at all levels. I shall recommend this for a Masters programme, rather than the undergraduate programme I initially thought to use it with. The style and philosophy of the text is more suited to those students applying statistics to Sport at M-level This is a really useful and interesting application of quantitative methods that I have recommended to my students. Given the general focus of the course on social research perspectives I cannot recommend it as essential reading as it only covers a couple of lectures / seminars. For those students wanting to explore quantitative data further through their MA′s I have no hesitation in recommending this as both accessible and thought-provoking. A very interesting book for those who want to specialise in qualitative data analysis. David Byrne′s book provides a useful theoretical/descriptive approach to the subject, usefully bridging the gap between the nuts and bolts stage of doing statistics and the way the "knowledge" is subsequently (ab)used in society. While some students will dismiss statistics out of hand (through terror of maths, usually), those who do get hooked, on the other hand, often become seduced by the seemingly awesome and indisputable importance of their "objective" numerical outputs. This book should convince both camps that numbers can indeed tell us useful things about the world, but that without a solid interpretation they are fairly worthless.
There is probably too much detail here for my introductory course in quantitative research, but particularly the first six chapters contain much material that is useful for this level. The chapters are of manageable size and contain pertinent examples from the social sciences. This is a useful text but rather too detailed for undergraduate students. I will, however, recommend it as supplementary reading to Masters′ Level students.