Interpreting Quantitative Data

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).

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.

• IntroductionInterpreting the Real and Describing the ComplexWhy We Have to MeasureThe Nature of MeasurementWhat We Measure and How We MeasureThe State′s MeasurementThe Construction and Use of Official StatisticsMeasuring the Complex WorldThe Character of Social SurveysProbability and Quantitative ReasoningInterpreting MeasurementsExploring, Describing and ClassifyingLinear ModellingClues as to CausesCoping with Non-Linearity and EmergenceSimulation and Neural NetsQualitative ModellingIssues of Meaning and CauseConclusion